/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // Intel License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000, Intel Corporation, all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of Intel Corporation may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // // 2011 Jason Newton // 2016 Costantino Grama // 2016 Federico Bolelli // 2016 Lorenzo Baraldi // 2016 Roberto Vezzani // 2016 Michele Cancilla //M*/ // #include "precomp.hpp" #include namespace cv{ namespace connectedcomponents{ struct NoOp{ NoOp(){ } inline void init(int /*labels*/){ } inline void initElement(const int /*nlabels*/){ } inline void operator()(int r, int c, int l){ (void)r; (void)c; (void)l; } void finish(){} inline void setNextLoc(const int /*nextLoc*/){ } inline static void mergeStats(const cv::Mat& /*imgLabels*/, NoOp* /*sopArray*/, NoOp& /*sop*/, const int& /*nLabels*/){ } }; struct Point2ui64{ uint64 x, y; Point2ui64(uint64 _x, uint64 _y) :x(_x), y(_y){} }; struct CCStatsOp{ const _OutputArray* _mstatsv; cv::Mat statsv; const _OutputArray* _mcentroidsv; cv::Mat centroidsv; std::vector integrals; int _nextLoc; CCStatsOp(){} CCStatsOp(OutputArray _statsv, OutputArray _centroidsv) : _mstatsv(&_statsv), _mcentroidsv(&_centroidsv){} inline void init(int nlabels){ _mstatsv->create(cv::Size(CC_STAT_MAX, nlabels), cv::DataType::type); statsv = _mstatsv->getMat(); _mcentroidsv->create(cv::Size(2, nlabels), cv::DataType::type); centroidsv = _mcentroidsv->getMat(); for (int l = 0; l < (int)nlabels; ++l){ int *row = (int *)&statsv.at(l, 0); row[CC_STAT_LEFT] = INT_MAX; row[CC_STAT_TOP] = INT_MAX; row[CC_STAT_WIDTH] = INT_MIN; row[CC_STAT_HEIGHT] = INT_MIN; row[CC_STAT_AREA] = 0; } integrals.resize(nlabels, Point2ui64(0, 0)); } inline void initElement(const int nlabels){ statsv = cv::Mat(nlabels, CC_STAT_MAX, cv::DataType::type); for (int l = 0; l < (int)nlabels; ++l){ int *row = (int *)statsv.ptr(l); row[CC_STAT_LEFT] = INT_MAX; row[CC_STAT_TOP] = INT_MAX; row[CC_STAT_WIDTH] = INT_MIN; row[CC_STAT_HEIGHT] = INT_MIN; row[CC_STAT_AREA] = 0; } integrals.resize(nlabels, Point2ui64(0, 0)); } void operator()(int r, int c, int l){ int *row = &statsv.at(l, 0); row[CC_STAT_LEFT] = MIN(row[CC_STAT_LEFT], c); row[CC_STAT_WIDTH] = MAX(row[CC_STAT_WIDTH], c); row[CC_STAT_TOP] = MIN(row[CC_STAT_TOP], r); row[CC_STAT_HEIGHT] = MAX(row[CC_STAT_HEIGHT], r); row[CC_STAT_AREA]++; Point2ui64 &integral = integrals[l]; integral.x += c; integral.y += r; } void finish(){ for (int l = 0; l < statsv.rows; ++l){ int *row = &statsv.at(l, 0); row[CC_STAT_WIDTH] = row[CC_STAT_WIDTH] - row[CC_STAT_LEFT] + 1; row[CC_STAT_HEIGHT] = row[CC_STAT_HEIGHT] - row[CC_STAT_TOP] + 1; Point2ui64 &integral = integrals[l]; double *centroid = ¢roidsv.at(l, 0); double area = ((unsigned*)row)[CC_STAT_AREA]; centroid[0] = double(integral.x) / area; centroid[1] = double(integral.y) / area; } } inline void setNextLoc(const int nextLoc){ _nextLoc = nextLoc; } inline static void mergeStats(const cv::Mat &imgLabels, CCStatsOp *SopArray, CCStatsOp &sop, const int &nLabels){ const int h = imgLabels.rows; if (sop._nextLoc != h){ for (int nextLoc = sop._nextLoc; nextLoc < h; nextLoc = SopArray[nextLoc]._nextLoc){ //merge between sopNext and sop for (int l = 0; l < nLabels; ++l){ int *rowNext = (int*)SopArray[nextLoc].statsv.ptr(l); if (rowNext[CC_STAT_AREA] > 0){ //if changed merge all the stats int *rowMerged = (int*)sop.statsv.ptr(l); rowMerged[CC_STAT_LEFT] = MIN(rowMerged[CC_STAT_LEFT], rowNext[CC_STAT_LEFT]); rowMerged[CC_STAT_WIDTH] = MAX(rowMerged[CC_STAT_WIDTH], rowNext[CC_STAT_WIDTH]); rowMerged[CC_STAT_TOP] = MIN(rowMerged[CC_STAT_TOP], rowNext[CC_STAT_TOP]); rowMerged[CC_STAT_HEIGHT] = MAX(rowMerged[CC_STAT_HEIGHT], rowNext[CC_STAT_HEIGHT]); rowMerged[CC_STAT_AREA] += rowNext[CC_STAT_AREA]; sop.integrals[l].x += SopArray[nextLoc].integrals[l].x; sop.integrals[l].y += SopArray[nextLoc].integrals[l].y; } } } } } }; //Find the root of the tree of node i template inline static LabelT findRoot(const LabelT *P, LabelT i){ LabelT root = i; while (P[root] < root){ root = P[root]; } return root; } //Make all nodes in the path of node i point to root template inline static void setRoot(LabelT *P, LabelT i, LabelT root){ while (P[i] < i){ LabelT j = P[i]; P[i] = root; i = j; } P[i] = root; } //Find the root of the tree of the node i and compress the path in the process template inline static LabelT find(LabelT *P, LabelT i){ LabelT root = findRoot(P, i); setRoot(P, i, root); return root; } //unite the two trees containing nodes i and j and return the new root template inline static LabelT set_union(LabelT *P, LabelT i, LabelT j){ LabelT root = findRoot(P, i); if (i != j){ LabelT rootj = findRoot(P, j); if (root > rootj){ root = rootj; } setRoot(P, j, root); } setRoot(P, i, root); return root; } //Flatten the Union Find tree and relabel the components template inline static LabelT flattenL(LabelT *P, LabelT length){ LabelT k = 1; for (LabelT i = 1; i < length; ++i){ if (P[i] < i){ P[i] = P[P[i]]; } else{ P[i] = k; k = k + 1; } } return k; } template inline static void flattenL(LabelT *P, const int start, const int nElem, LabelT &k){ for (int i = start; i < start + nElem; ++i){ if (P[i] < i){//node that point to root P[i] = P[P[i]]; } else{ //for root node P[i] = k; k = k + 1; } } } //Based on "Two Strategies to Speed up Connected Components Algorithms", the SAUF (Scan array union find) variant //using decision trees //Kesheng Wu, et al template struct LabelingWuParallel{ class FirstScan8Connectivity : public cv::ParallelLoopBody{ const cv::Mat &_img; cv::Mat &_imgLabels; LabelT *_P; int *_chunksSizeAndLabels; public: FirstScan8Connectivity(const cv::Mat &img, cv::Mat &imgLabels, LabelT *P, int *chunksSizeAndLabels) : _img(img), _imgLabels(imgLabels), _P(P), _chunksSizeAndLabels(chunksSizeAndLabels){} FirstScan8Connectivity & operator=(const FirstScan8Connectivity &) { return *this; } void operator()(const cv::Range &range) const{ int r = range.start; _chunksSizeAndLabels[r] = range.end; LabelT label = LabelT(r * _imgLabels.cols / 4 + 1); const LabelT firstLabel = label; const int w = _img.cols; const int limitLine = r, startR = r; // Rosenfeld Mask // +-+-+-+ // |p|q|r| // +-+-+-+ // |s|x| // +-+-+ for (; r != range.end; ++r) { PixelT const * const img_row = _img.ptr(r); PixelT const * const img_row_prev = (PixelT *)(((char *)img_row) - _img.step.p[0]); LabelT * const imgLabels_row = _imgLabels.ptr(r); LabelT * const imgLabels_row_prev = (LabelT *)(((char *)imgLabels_row) - _imgLabels.step.p[0]); for (int c = 0; c < w; ++c) { #define condition_p c > 0 && r > limitLine && img_row_prev[c - 1] > 0 #define condition_q r > limitLine && img_row_prev[c] > 0 #define condition_r c < w - 1 && r > limitLine && img_row_prev[c + 1] > 0 #define condition_s c > 0 && img_row[c - 1] > 0 #define condition_x img_row[c] > 0 if (condition_x){ if (condition_q){ //copy q imgLabels_row[c] = imgLabels_row_prev[c]; } else{ //not q if (condition_r){ if (condition_p){ //concavity p->x->r. Merge imgLabels_row[c] = set_union(_P, imgLabels_row_prev[c - 1], imgLabels_row_prev[c + 1]); } else{ //not p and q if (condition_s){ //step s->x->r. Merge imgLabels_row[c] = set_union(_P, imgLabels_row[c - 1], imgLabels_row_prev[c + 1]); } else{ //not p, q and s //copy r imgLabels_row[c] = imgLabels_row_prev[c + 1]; } } } else{ //not r and q if (condition_p){ //copy p imgLabels_row[c] = imgLabels_row_prev[c - 1]; } else{//not r,q and p if (condition_s){ imgLabels_row[c] = imgLabels_row[c - 1]; } else{ //new label imgLabels_row[c] = label; _P[label] = label; label = label + 1; } } } } } else{ //x is a background pixel imgLabels_row[c] = 0; } } } //write in the follower memory location _chunksSizeAndLabels[startR + 1] = label - firstLabel; } #undef condition_p #undef condition_q #undef condition_r #undef condition_s #undef condition_x }; class FirstScan4Connectivity : public cv::ParallelLoopBody{ const cv::Mat &_img; cv::Mat &_imgLabels; LabelT *_P; int *_chunksSizeAndLabels; public: FirstScan4Connectivity(const cv::Mat &img, cv::Mat &imgLabels, LabelT *P, int *chunksSizeAndLabels) : _img(img), _imgLabels(imgLabels), _P(P), _chunksSizeAndLabels(chunksSizeAndLabels){} FirstScan4Connectivity & operator=(const FirstScan4Connectivity &) { return *this; } void operator()(const cv::Range &range) const{ int r = range.start; _chunksSizeAndLabels[r] = range.end; LabelT label = LabelT(r * _imgLabels.cols / 4 + 1); const LabelT firstLabel = label; const int w = _img.cols; const int limitLine = r, startR = r; // Rosenfeld Mask // +-+-+-+ // |-|q|-| // +-+-+-+ // |s|x| // +-+-+ for (; r != range.end; ++r){ PixelT const * const img_row = _img.ptr(r); PixelT const * const img_row_prev = (PixelT *)(((char *)img_row) - _img.step.p[0]); LabelT * const imgLabels_row = _imgLabels.ptr(r); LabelT * const imgLabels_row_prev = (LabelT *)(((char *)imgLabels_row) - _imgLabels.step.p[0]); for (int c = 0; c < w; ++c) { #define condition_q r > limitLine && img_row_prev[c] > 0 #define condition_s c > 0 && img_row[c - 1] > 0 #define condition_x img_row[c] > 0 if (condition_x){ if (condition_q){ if (condition_s){ //step s->x->q. Merge imgLabels_row[c] = set_union(_P, imgLabels_row[c - 1], imgLabels_row_prev[c]); } else{ //copy q imgLabels_row[c] = imgLabels_row_prev[c]; } } else{ if (condition_s){ // copy s imgLabels_row[c] = imgLabels_row[c - 1]; } else{ //new label imgLabels_row[c] = label; _P[label] = label; label = label + 1; } } } else{ //x is a background pixel imgLabels_row[c] = 0; } } } //write in the following memory location _chunksSizeAndLabels[startR + 1] = label - firstLabel; } #undef condition_q #undef condition_s #undef condition_x }; class SecondScan : public cv::ParallelLoopBody{ cv::Mat &_imgLabels; const LabelT *_P; StatsOp &_sop; StatsOp *_sopArray; LabelT &_nLabels; public: SecondScan(cv::Mat &imgLabels, const LabelT *P, StatsOp &sop, StatsOp *SopArray, LabelT &nLabels) : _imgLabels(imgLabels), _P(P), _sop(sop), _sopArray(SopArray), _nLabels(nLabels){} SecondScan & operator=(const SecondScan &) { return *this; } void operator()(const cv::Range &range) const{ int r = range.start; const int rowBegin = r; const int rowEnd = range.end; if (rowBegin > 0){ _sopArray[rowBegin].initElement(_nLabels); _sopArray[rowBegin].setNextLoc(rowEnd); //_nextLoc = rowEnd; for (; r < rowEnd; ++r) { LabelT * img_row_start = _imgLabels.ptr(r); LabelT * const img_row_end = img_row_start + _imgLabels.cols; for (int c = 0; img_row_start != img_row_end; ++img_row_start, ++c){ *img_row_start = _P[*img_row_start]; _sopArray[rowBegin](r, c, *img_row_start); } } } else{ //the first thread uses sop in order to make less merges _sop.setNextLoc(rowEnd); for (; r < rowEnd; ++r) { LabelT * img_row_start = _imgLabels.ptr(r); LabelT * const img_row_end = img_row_start + _imgLabels.cols; for (int c = 0; img_row_start != img_row_end; ++img_row_start, ++c){ *img_row_start = _P[*img_row_start]; _sop(r, c, *img_row_start); } } } } }; inline static void mergeLabels8Connectivity(cv::Mat &imgLabels, LabelT *P, const int *chunksSizeAndLabels){ // Merge Mask // +-+-+-+ // |p|q|r| // +-+-+-+ // |x| // +-+ const int w = imgLabels.cols, h = imgLabels.rows; for (int r = chunksSizeAndLabels[0]; r < h; r = chunksSizeAndLabels[r]){ LabelT * const imgLabels_row = imgLabels.ptr(r); LabelT * const imgLabels_row_prev = (LabelT *)(((char *)imgLabels_row) - imgLabels.step.p[0]); for (int c = 0; c < w; ++c){ #define condition_p c > 0 && imgLabels_row_prev[c - 1] > 0 #define condition_q imgLabels_row_prev[c] > 0 #define condition_r c < w - 1 && imgLabels_row_prev[c + 1] > 0 #define condition_x imgLabels_row[c] > 0 if (condition_x){ if (condition_p){ //merge of two label imgLabels_row[c] = set_union(P, imgLabels_row_prev[c - 1], imgLabels_row[c]); } if (condition_r){ //merge of two label imgLabels_row[c] = set_union(P, imgLabels_row_prev[c + 1], imgLabels_row[c]); } if (condition_q){ //merge of two label imgLabels_row[c] = set_union(P, imgLabels_row_prev[c], imgLabels_row[c]); } } } } #undef condition_p #undef condition_q #undef condition_r #undef condition_x } inline static void mergeLabels4Connectivity(cv::Mat &imgLabels, LabelT *P, const int *chunksSizeAndLabels){ // Merge Mask // +-+-+-+ // |-|q|-| // +-+-+-+ // |x| // +-+ const int w = imgLabels.cols, h = imgLabels.rows; for (int r = chunksSizeAndLabels[0]; r < h; r = chunksSizeAndLabels[r]){ LabelT * const imgLabels_row = imgLabels.ptr(r); LabelT * const imgLabels_row_prev = (LabelT *)(((char *)imgLabels_row) - imgLabels.step.p[0]); for (int c = 0; c < w; ++c){ #define condition_q imgLabels_row_prev[c] > 0 #define condition_x imgLabels_row[c] > 0 if (condition_x){ if (condition_q){ //merge of two label imgLabels_row[c] = set_union(P, imgLabels_row_prev[c], imgLabels_row[c]); } } } } #undef condition_q #undef condition_x } LabelT operator()(const cv::Mat &img, cv::Mat &imgLabels, int connectivity, StatsOp &sop){ CV_Assert(img.rows == imgLabels.rows); CV_Assert(img.cols == imgLabels.cols); CV_Assert(connectivity == 8 || connectivity == 4); const int nThreads = cv::getNumThreads(); cv::setNumThreads(nThreads); const int h = img.rows; const int w = img.cols; //A quick and dirty upper bound for the maximimum number of labels. //Following formula comes from the fact that a 2x2 block in 4-way connectivity //labeling can never have more than 2 new labels and 1 label for background. //Worst case image example pattern: //1 0 1 0 1... //0 1 0 1 0... //1 0 1 0 1... //............ //Obviously, 4-way connectivity upper bound is also good for 8-way connectivity labeling const size_t Plength = (size_t(h) * size_t(w) + 1) / 2 + 1; //Array used to store info and labeled pixel by each thread. //Different threads affect different memory location of chunksSizeAndLabels int *chunksSizeAndLabels = (int *)cv::fastMalloc(h * sizeof(int)); //Tree of labels LabelT *P = (LabelT *)cv::fastMalloc(Plength * sizeof(LabelT)); //First label is for background P[0] = 0; cv::Range range(0, h); if (connectivity == 8){ //First scan, each thread works with chunk of img.rows/nThreads rows //e.g. 300 rows, 4 threads -> each chunks is composed of 75 rows cv::parallel_for_(range, FirstScan8Connectivity(img, imgLabels, P, chunksSizeAndLabels), nThreads); //merge labels of different chunks mergeLabels8Connectivity(imgLabels, P, chunksSizeAndLabels); } else{ //First scan, each thread works with chunk of img.rows/nThreads rows //e.g. 300 rows, 4 threads -> each chunks is composed of 75 rows cv::parallel_for_(range, FirstScan4Connectivity(img, imgLabels, P, chunksSizeAndLabels), nThreads); //merge labels of different chunks mergeLabels4Connectivity(imgLabels, P, chunksSizeAndLabels); } LabelT nLabels = 1; for (int i = 0; i < h; i = chunksSizeAndLabels[i]){ flattenL(P, i * w / 4 + 1, chunksSizeAndLabels[i + 1], nLabels); } //Array for statistics dataof threads StatsOp *SopArray = new StatsOp[h]; sop.init(nLabels); //Second scan cv::parallel_for_(range, SecondScan(imgLabels, P, sop, SopArray, nLabels), nThreads); StatsOp::mergeStats(imgLabels, SopArray, sop, nLabels); sop.finish(); delete[] SopArray; cv::fastFree(chunksSizeAndLabels); cv::fastFree(P); return nLabels; } };//End struct LabelingWuParallel //Based on "Two Strategies to Speed up Connected Components Algorithms", the SAUF (Scan array union find) variant //using decision trees //Kesheng Wu, et al template struct LabelingWu{ LabelT operator()(const cv::Mat &img, cv::Mat &imgLabels, int connectivity, StatsOp &sop){ CV_Assert(imgLabels.rows == img.rows); CV_Assert(imgLabels.cols == img.cols); CV_Assert(connectivity == 8 || connectivity == 4); const int h = img.rows; const int w = img.cols; //A quick and dirty upper bound for the maximimum number of labels. //Following formula comes from the fact that a 2x2 block in 4-way connectivity //labeling can never have more than 2 new labels and 1 label for background. //Worst case image example pattern: //1 0 1 0 1... //0 1 0 1 0... //1 0 1 0 1... //............ //Obviously, 4-way connectivity upper bound is also good for 8-way connectivity labeling const size_t Plength = (size_t(h) * size_t(w) + 1) / 2 + 1; //array P for equivalences resolution LabelT *P = (LabelT *)fastMalloc(sizeof(LabelT)* Plength); //first label is for background pixels P[0] = 0; LabelT lunique = 1; if (connectivity == 8){ for (int r = 0; r < h; ++r){ // Get row pointers PixelT const * const img_row = img.ptr(r); PixelT const * const img_row_prev = (PixelT *)(((char *)img_row) - img.step.p[0]); LabelT * const imgLabels_row = imgLabels.ptr(r); LabelT * const imgLabels_row_prev = (LabelT *)(((char *)imgLabels_row) - imgLabels.step.p[0]); for (int c = 0; c < w; ++c){ #define condition_p c>0 && r>0 && img_row_prev[c - 1]>0 #define condition_q r>0 && img_row_prev[c]>0 #define condition_r c < w - 1 && r > 0 && img_row_prev[c + 1] > 0 #define condition_s c > 0 && img_row[c - 1] > 0 #define condition_x img_row[c] > 0 if (condition_x){ if (condition_q){ //x <- q imgLabels_row[c] = imgLabels_row_prev[c]; } else{ // q = 0 if (condition_r){ if (condition_p){ // x <- merge(p,r) imgLabels_row[c] = set_union(P, imgLabels_row_prev[c - 1], imgLabels_row_prev[c + 1]); } else{ // p = q = 0 if (condition_s){ // x <- merge(s,r) imgLabels_row[c] = set_union(P, imgLabels_row[c - 1], imgLabels_row_prev[c + 1]); } else{ // p = q = s = 0 // x <- r imgLabels_row[c] = imgLabels_row_prev[c + 1]; } } } else{ // r = q = 0 if (condition_p){ // x <- p imgLabels_row[c] = imgLabels_row_prev[c - 1]; } else{ // r = q = p = 0 if (condition_s){ imgLabels_row[c] = imgLabels_row[c - 1]; } else{ //new label imgLabels_row[c] = lunique; P[lunique] = lunique; lunique = lunique + 1; } } } } } else{ //x is a background pixel imgLabels_row[c] = 0; } } } #undef condition_p #undef condition_q #undef condition_r #undef condition_s #undef condition_x } else{ for (int r = 0; r < h; ++r){ PixelT const * const img_row = img.ptr(r); PixelT const * const img_row_prev = (PixelT *)(((char *)img_row) - img.step.p[0]); LabelT * const imgLabels_row = imgLabels.ptr(r); LabelT * const imgLabels_row_prev = (LabelT *)(((char *)imgLabels_row) - imgLabels.step.p[0]); for (int c = 0; c < w; ++c) { #define condition_q r > 0 && img_row_prev[c] > 0 #define condition_s c > 0 && img_row[c - 1] > 0 #define condition_x img_row[c] > 0 if (condition_x){ if (condition_q){ if (condition_s){ //Merge s->x->q imgLabels_row[c] = set_union(P, imgLabels_row[c - 1], imgLabels_row_prev[c]); } else{ //copy q imgLabels_row[c] = imgLabels_row_prev[c]; } } else{ if (condition_s){ // copy s imgLabels_row[c] = imgLabels_row[c - 1]; } else{ //new label imgLabels_row[c] = lunique; P[lunique] = lunique; lunique = lunique + 1; } } } else{ //x is a background pixel imgLabels_row[c] = 0; } } } #undef condition_q #undef condition_s #undef condition_x } //analysis LabelT nLabels = flattenL(P, lunique); sop.init(nLabels); for (int r = 0; r < h; ++r) { LabelT * img_row_start = imgLabels.ptr(r); LabelT * const img_row_end = img_row_start + w; for (int c = 0; img_row_start != img_row_end; ++img_row_start, ++c){ *img_row_start = P[*img_row_start]; sop(r, c, *img_row_start); } } sop.finish(); fastFree(P); return nLabels; }//End function LabelingWu operator() };//End struct LabelingWu // Based on “Optimized Block-based Connected Components Labeling with Decision Trees”, Costantino Grana et al // Only for 8-connectivity template struct LabelingGranaParallel{ class FirstScan : public cv::ParallelLoopBody{ private: const cv::Mat &_img; cv::Mat &_imgLabels; LabelT *_P; int *_chunksSizeAndLabels; public: FirstScan(const cv::Mat &img, cv::Mat &imgLabels, LabelT *P, int *chunksSizeAndLabels) : _img(img), _imgLabels(imgLabels), _P(P), _chunksSizeAndLabels(chunksSizeAndLabels){} FirstScan & operator=(const FirstScan&) { return *this; } void operator()(const cv::Range &range) const{ int r = range.start; r += (r % 2); _chunksSizeAndLabels[r] = range.end + (range.end % 2); LabelT label = LabelT(r * _imgLabels.cols / 4 + 1); const LabelT firstLabel = label; const int h = _img.rows, w = _img.cols; const int limitLine = r + 1, startR = r; for (; r < range.end; r += 2){ // Get rows pointer const PixelT * const img_row = _img.ptr(r); const PixelT * const img_row_prev = (PixelT *)(((char *)img_row) - _img.step.p[0]); const PixelT * const img_row_prev_prev = (PixelT *)(((char *)img_row_prev) - _img.step.p[0]); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + _img.step.p[0]); LabelT * const imgLabels_row = _imgLabels.ptr(r); LabelT * const imgLabels_row_prev_prev = (LabelT *)(((char *)imgLabels_row) - _imgLabels.step.p[0] - _imgLabels.step.p[0]); for (int c = 0; c < w; c += 2) { // We work with 2x2 blocks // +-+-+-+ // |P|Q|R| // +-+-+-+ // |S|X| // +-+-+ // The pixels are named as follows // +---+---+---+ // |a b|c d|e f| // |g h|i j|k l| // +---+---+---+ // |m n|o p| // |q r|s t| // +---+---+ // Pixels a, f, l, q are not needed, since we need to understand the // the connectivity between these blocks and those pixels only metter // when considering the outer connectivities // A bunch of defines used to check if the pixels are foreground, // without going outside the image limits. #define condition_b c-1>=0 && r > limitLine && img_row_prev_prev[c-1]>0 #define condition_c r > limitLine && img_row_prev_prev[c]>0 #define condition_d c+1 limitLine && img_row_prev_prev[c+1]>0 #define condition_e c+2 limitLine && img_row_prev_prev[c+2]>0 #define condition_g c-2>=0 && r > limitLine - 1 && img_row_prev[c-2]>0 #define condition_h c-1>=0 && r > limitLine - 1 && img_row_prev[c-1]>0 #define condition_i r > limitLine - 1 && img_row_prev[c]>0 #define condition_j c+1 limitLine - 1 && img_row_prev[c+1]>0 #define condition_k c+2 limitLine - 1 && img_row_prev[c+2]>0 #define condition_m c-2>=0 && img_row[c-2]>0 #define condition_n c-1>=0 && img_row[c-1]>0 #define condition_o img_row[c]>0 #define condition_p c+10 #define condition_r c-1>=0 && r+10 #define condition_s r+10 #define condition_t c+10 // This is a decision tree which allows to choose which action to // perform, checking as few conditions as possible. // Actions are available after the tree. if (condition_o) { if (condition_n) { if (condition_j) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { if (condition_h) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { if (condition_p) { if (condition_k) { if (condition_d) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { if (condition_h) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } } else { if (condition_r) { if (condition_j) { if (condition_m) { if (condition_h) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { if (condition_g) { if (condition_b) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { if (condition_i) { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } else { if (condition_h) { if (condition_c) { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } else { //Action_14: Merge labels of block _P, Q and S imgLabels_row[c] = set_union(_P, set_union(_P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c]), imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } } else { if (condition_p) { if (condition_k) { if (condition_m) { if (condition_h) { if (condition_d) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { if (condition_d) { if (condition_g) { if (condition_b) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { if (condition_i) { if (condition_g) { if (condition_b) { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(_P, set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(_P, set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } } else { if (condition_i) { if (condition_d) { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(_P, set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { if (condition_h) { if (condition_d) { if (condition_c) { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } else { //Action_15: Merge labels of block _P, R and S imgLabels_row[c] = set_union(_P, set_union(_P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_15: Merge labels of block _P, R and S imgLabels_row[c] = set_union(_P, set_union(_P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } } else { if (condition_h) { if (condition_m) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { // ACTION_9 Merge labels of block _P and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c - 2], imgLabels_row[c - 2]); continue; } } else { if (condition_i) { if (condition_m) { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } } } else { if (condition_h) { if (condition_m) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { // ACTION_9 Merge labels of block _P and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c - 2], imgLabels_row[c - 2]); continue; } } else { if (condition_i) { if (condition_m) { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } } } } else { if (condition_j) { if (condition_i) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { if (condition_h) { if (condition_c) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { //Action_7: Merge labels of block _P and Q imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c]); continue; } } else { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } } } else { if (condition_p) { if (condition_k) { if (condition_i) { if (condition_d) { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } else { // ACTION_10 Merge labels of block Q and R imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]); continue; } } else { if (condition_h) { if (condition_d) { if (condition_c) { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } else { //Action_8: Merge labels of block _P and R imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c + 2]); continue; } } else { //Action_8: Merge labels of block _P and R imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c + 2]); continue; } } else { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } } } else { if (condition_i) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { if (condition_h) { //Action_3: Assign label of block _P imgLabels_row[c] = imgLabels_row_prev_prev[c - 2]; continue; } else { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = label; _P[label] = label; label = label + 1; continue; } } } } else { if (condition_i) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { if (condition_h) { //Action_3: Assign label of block _P imgLabels_row[c] = imgLabels_row_prev_prev[c - 2]; continue; } else { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = label; _P[label] = label; label = label + 1; continue; } } } } } } } else { if (condition_s) { if (condition_p) { if (condition_n) { if (condition_j) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { if (condition_h) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { if (condition_k) { if (condition_d) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { if (condition_h) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } } else { if (condition_r) { if (condition_j) { if (condition_m) { if (condition_h) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { if (condition_g) { if (condition_b) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { if (condition_k) { if (condition_d) { if (condition_m) { if (condition_h) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { if (condition_g) { if (condition_b) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { if (condition_i) { if (condition_m) { if (condition_h) { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } else { if (condition_g) { if (condition_b) { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(_P, set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(_P, set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(_P, set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { if (condition_i) { if (condition_m) { if (condition_h) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } } } else { if (condition_j) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { if (condition_k) { if (condition_i) { if (condition_d) { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } else { // ACTION_10 Merge labels of block Q and R imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]); continue; } } else { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } } else { if (condition_i) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = label; _P[label] = label; label = label + 1; continue; } } } } } } else { if (condition_r) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_n) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = label; _P[label] = label; label = label + 1; continue; } } } } else { if (condition_p) { if (condition_j) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { if (condition_k) { if (condition_i) { if (condition_d) { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } else { // ACTION_10 Merge labels of block Q and R imgLabels_row[c] = set_union(_P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]); continue; } } else { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } } else { if (condition_i) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = label; _P[label] = label; label = label + 1; continue; } } } } else { if (condition_t) { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = label; _P[label] = label; label = label + 1; continue; } else { // Action_1: No action (the block has no foreground pixels) imgLabels_row[c] = 0; continue; } } } } } } //write in the follower memory location _chunksSizeAndLabels[startR + 1] = label - firstLabel; } #undef condition_k #undef condition_j #undef condition_i #undef condition_h #undef condition_g #undef condition_e #undef condition_d #undef condition_c #undef condition_b }; class SecondScan : public cv::ParallelLoopBody{ private: const cv::Mat &_img; cv::Mat &_imgLabels; LabelT *_P; StatsOp &_sop; StatsOp *_sopArray; LabelT &_nLabels; public: SecondScan(const cv::Mat &img, cv::Mat &imgLabels, LabelT *P, StatsOp &sop, StatsOp *SopArray, LabelT &nLabels) : _img(img), _imgLabels(imgLabels), _P(P), _sop(sop), _sopArray(SopArray), _nLabels(nLabels){} SecondScan & operator=(const SecondScan &) { return *this; } void operator()(const cv::Range &range) const{ int r = range.start; r += (r % 2); const int rowBegin = r; const int rowEnd = range.end + range.end % 2; if (rowBegin > 0){ _sopArray[rowBegin].initElement(_nLabels); _sopArray[rowBegin].setNextLoc(rowEnd); //_nextLoc = rowEnd; if (_imgLabels.rows & 1){ if (_imgLabels.cols & 1){ //Case 1: both rows and cols odd for (; r < rowEnd; r += 2){ // Get rows pointer const PixelT * const img_row = _img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + _img.step.p[0]); LabelT * const imgLabels_row = _imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + _imgLabels.step.p[0]); // Get rows pointer for (int c = 0; c < _imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = _P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; _sopArray[rowBegin](r, c, iLabel); } else{ imgLabels_row[c] = 0; _sopArray[rowBegin](r, c, 0); } if (c + 1 < _imgLabels.cols) { if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; _sopArray[rowBegin](r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; _sopArray[rowBegin](r, c + 1, 0); } if (r + 1 < _imgLabels.rows) { if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; _sopArray[rowBegin](r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; _sopArray[rowBegin](r + 1, c, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; _sopArray[rowBegin](r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; _sopArray[rowBegin](r + 1, c + 1, 0); } } } else if (r + 1 < _imgLabels.rows) { if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; _sopArray[rowBegin](r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; _sopArray[rowBegin](r + 1, c, 0); } } } else { imgLabels_row[c] = 0; _sopArray[rowBegin](r, c, 0); if (c + 1 < _imgLabels.cols) { imgLabels_row[c + 1] = 0; _sopArray[rowBegin](r, c + 1, 0); if (r + 1 < _imgLabels.rows) { imgLabels_row_fol[c] = 0; imgLabels_row_fol[c + 1] = 0; _sopArray[rowBegin](r + 1, c, 0); _sopArray[rowBegin](r + 1, c + 1, 0); } } else if (r + 1 < _imgLabels.rows) { imgLabels_row_fol[c] = 0; _sopArray[rowBegin](r + 1, c, 0); } } } } }//END Case 1 else{ //Case 2: only rows odd for (; r < rowEnd; r += 2){ // Get rows pointer const PixelT * const img_row = _img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + _img.step.p[0]); LabelT * const imgLabels_row = _imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + _imgLabels.step.p[0]); // Get rows pointer for (int c = 0; c < _imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = _P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; _sopArray[rowBegin](r, c, iLabel); } else{ imgLabels_row[c] = 0; _sopArray[rowBegin](r, c, 0); } if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; _sopArray[rowBegin](r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; _sopArray[rowBegin](r, c + 1, 0); } if (r + 1 < _imgLabels.rows) { if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; _sopArray[rowBegin](r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; _sopArray[rowBegin](r + 1, c, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; _sopArray[rowBegin](r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; _sopArray[rowBegin](r + 1, c + 1, 0); } } } else { imgLabels_row[c] = 0; imgLabels_row[c + 1] = 0; _sopArray[rowBegin](r, c, 0); _sopArray[rowBegin](r, c + 1, 0); if (r + 1 < _imgLabels.rows) { imgLabels_row_fol[c] = 0; imgLabels_row_fol[c + 1] = 0; _sopArray[rowBegin](r + 1, c, 0); _sopArray[rowBegin](r + 1, c + 1, 0); } } } } }// END Case 2 } else{ if (_imgLabels.cols & 1){ //Case 3: only cols odd for (; r < rowEnd; r += 2){ // Get rows pointer const PixelT * const img_row = _img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + _img.step.p[0]); LabelT * const imgLabels_row = _imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + _imgLabels.step.p[0]); // Get rows pointer for (int c = 0; c < _imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = _P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; _sopArray[rowBegin](r, c, iLabel); } else{ imgLabels_row[c] = 0; _sopArray[rowBegin](r, c, 0); } if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; _sopArray[rowBegin](r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; _sopArray[rowBegin](r + 1, c, 0); } if (c + 1 < _imgLabels.cols) { if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; _sopArray[rowBegin](r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; _sopArray[rowBegin](r, c + 1, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; _sopArray[rowBegin](r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; _sopArray[rowBegin](r + 1, c + 1, 0); } } } else{ imgLabels_row[c] = 0; imgLabels_row_fol[c] = 0; _sopArray[rowBegin](r, c, 0); _sopArray[rowBegin](r + 1, c, 0); if (c + 1 < _imgLabels.cols) { imgLabels_row[c + 1] = 0; imgLabels_row_fol[c + 1] = 0; _sopArray[rowBegin](r, c + 1, 0); _sopArray[rowBegin](r + 1, c + 1, 0); } } } } }// END case 3 else{ //Case 4: nothing odd for (; r < rowEnd; r += 2){ // Get rows pointer const PixelT * const img_row = _img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + _img.step.p[0]); LabelT * const imgLabels_row = _imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + _imgLabels.step.p[0]); // Get rows pointer for (int c = 0; c < _imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = _P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; _sopArray[rowBegin](r, c, iLabel); } else{ imgLabels_row[c] = 0; _sopArray[rowBegin](r, c, 0); } if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; _sopArray[rowBegin](r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; _sopArray[rowBegin](r, c + 1, 0); } if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; _sopArray[rowBegin](r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; _sopArray[rowBegin](r + 1, c, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; _sopArray[rowBegin](r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; _sopArray[rowBegin](r + 1, c + 1, 0); } } else { imgLabels_row[c] = 0; imgLabels_row[c + 1] = 0; imgLabels_row_fol[c] = 0; imgLabels_row_fol[c + 1] = 0; _sopArray[rowBegin](r, c, 0); _sopArray[rowBegin](r, c + 1, 0); _sopArray[rowBegin](r + 1, c, 0); _sopArray[rowBegin](r + 1, c + 1, 0); } } }//END case 4 } } } else{ //the first thread uses sop in order to make less merges _sop.setNextLoc(rowEnd); if (_imgLabels.rows & 1){ if (_imgLabels.cols & 1){ //Case 1: both rows and cols odd for (; r < rowEnd; r += 2){ // Get rows pointer const PixelT * const img_row = _img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + _img.step.p[0]); LabelT * const imgLabels_row = _imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + _imgLabels.step.p[0]); // Get rows pointer for (int c = 0; c < _imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = _P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; _sop(r, c, iLabel); } else{ imgLabels_row[c] = 0; _sop(r, c, 0); } if (c + 1 < _imgLabels.cols) { if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; _sop(r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; _sop(r, c + 1, 0); } if (r + 1 < _imgLabels.rows) { if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; _sop(r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; _sop(r + 1, c, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; _sop(r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; _sop(r + 1, c + 1, 0); } } } else if (r + 1 < _imgLabels.rows) { if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; _sop(r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; _sop(r + 1, c, 0); } } } else { imgLabels_row[c] = 0; _sop(r, c, 0); if (c + 1 < _imgLabels.cols) { imgLabels_row[c + 1] = 0; _sop(r, c + 1, 0); if (r + 1 < _imgLabels.rows) { imgLabels_row_fol[c] = 0; imgLabels_row_fol[c + 1] = 0; _sop(r + 1, c, 0); _sop(r + 1, c + 1, 0); } } else if (r + 1 < _imgLabels.rows) { imgLabels_row_fol[c] = 0; _sop(r + 1, c, 0); } } } } }//END Case 1 else{ //Case 2: only rows odd for (; r < rowEnd; r += 2){ // Get rows pointer const PixelT * const img_row = _img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + _img.step.p[0]); LabelT * const imgLabels_row = _imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + _imgLabels.step.p[0]); // Get rows pointer for (int c = 0; c < _imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = _P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; _sop(r, c, iLabel); } else{ imgLabels_row[c] = 0; _sop(r, c, 0); } if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; _sop(r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; _sop(r, c + 1, 0); } if (r + 1 < _imgLabels.rows) { if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; _sop(r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; _sop(r + 1, c, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; _sop(r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; _sop(r + 1, c + 1, 0); } } } else { imgLabels_row[c] = 0; imgLabels_row[c + 1] = 0; _sop(r, c, 0); _sop(r, c + 1, 0); if (r + 1 < _imgLabels.rows) { imgLabels_row_fol[c] = 0; imgLabels_row_fol[c + 1] = 0; _sop(r + 1, c, 0); _sop(r + 1, c + 1, 0); } } } } }// END Case 2 } else{ if (_imgLabels.cols & 1){ //Case 3: only cols odd for (; r < rowEnd; r += 2){ // Get rows pointer const PixelT * const img_row = _img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + _img.step.p[0]); LabelT * const imgLabels_row = _imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + _imgLabels.step.p[0]); // Get rows pointer for (int c = 0; c < _imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = _P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; _sop(r, c, iLabel); } else{ imgLabels_row[c] = 0; _sop(r, c, 0); } if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; _sop(r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; _sop(r + 1, c, 0); } if (c + 1 < _imgLabels.cols) { if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; _sop(r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; _sop(r, c + 1, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; _sop(r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; _sop(r + 1, c + 1, 0); } } } else{ imgLabels_row[c] = 0; imgLabels_row_fol[c] = 0; _sop(r, c, 0); _sop(r + 1, c, 0); if (c + 1 < _imgLabels.cols) { imgLabels_row[c + 1] = 0; imgLabels_row_fol[c + 1] = 0; _sop(r, c + 1, 0); _sop(r + 1, c + 1, 0); } } } } }// END case 3 else{ //Case 4: nothing odd for (; r < rowEnd; r += 2){ // Get rows pointer const PixelT * const img_row = _img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + _img.step.p[0]); LabelT * const imgLabels_row = _imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + _imgLabels.step.p[0]); // Get rows pointer for (int c = 0; c < _imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = _P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; _sop(r, c, iLabel); } else{ imgLabels_row[c] = 0; _sop(r, c, 0); } if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; _sop(r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; _sop(r, c + 1, 0); } if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; _sop(r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; _sop(r + 1, c, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; _sop(r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; _sop(r + 1, c + 1, 0); } } else { imgLabels_row[c] = 0; imgLabels_row[c + 1] = 0; imgLabels_row_fol[c] = 0; imgLabels_row_fol[c + 1] = 0; _sop(r, c, 0); _sop(r, c + 1, 0); _sop(r + 1, c, 0); _sop(r + 1, c + 1, 0); } } }//END case 4 } } } } }; inline static void mergeLabels(const cv::Mat &img, cv::Mat &imgLabels, LabelT *P, int *chunksSizeAndLabels){ // Merge Mask // +---+---+---+ // |P -|Q -|R -| // |- -|- -|- -| // +---+---+---+ // |X -| // |- -| // +---+ const int w = imgLabels.cols, h = imgLabels.rows; for (int r = chunksSizeAndLabels[0]; r < h; r = chunksSizeAndLabels[r]){ LabelT * const imgLabels_row = imgLabels.ptr(r); LabelT * const imgLabels_row_prev_prev = (LabelT *)(((char *)imgLabels_row) - imgLabels.step.p[0] - imgLabels.step.p[0]); const PixelT * const img_row = img.ptr(r); const PixelT * const img_row_prev = (PixelT *)(((char *)img_row) - img.step.p[0]); for (int c = 0; c < w; c += 2){ #define condition_x imgLabels_row[c] > 0 #define condition_pppr c > 1 && imgLabels_row_prev_prev[c - 2] > 0 #define condition_qppr imgLabels_row_prev_prev[c] > 0 #define condition_qppr1 c < w - 1 #define condition_qppr2 c < w #define condition_rppr c < w - 2 && imgLabels_row_prev_prev[c + 2] > 0 if (condition_x){ if (condition_pppr){ //check in img if (img_row[c] > 0 && img_row_prev[c - 1] > 0) //assign the same label imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c - 2], imgLabels_row[c]); } if (condition_qppr){ if (condition_qppr1){ if ((img_row[c] > 0 && img_row_prev[c] > 0) || (img_row[c + 1] > 0 && img_row_prev[c] > 0) || (img_row[c] > 0 && img_row_prev[c + 1] > 0) || (img_row[c + 1] > 0 && img_row_prev[c + 1] > 0)){ imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c]); } } else /*if (condition_qppr2)*/{ if (img_row[c] > 0 && img_row_prev[c] > 0) imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c]); } } if (condition_rppr){ if (img_row[c + 1] > 0 && img_row_prev[c + 2] > 0) imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c]); } } } } } LabelT operator()(const cv::Mat &img, cv::Mat &imgLabels, int connectivity, StatsOp &sop){ CV_Assert(img.rows == imgLabels.rows); CV_Assert(img.cols == imgLabels.cols); CV_Assert(connectivity == 8); const int nThreads = cv::getNumThreads(); cv::setNumThreads(nThreads); const int h = img.rows; const int w = img.cols; //A quick and dirty upper bound for the maximimum number of labels. //Following formula comes from the fact that a 2x2 block in 8-connectivity case //can never have more than 1 new label and 1 label for background. //Worst case image example pattern: //1 0 1 0 1... //0 0 0 0 0... //1 0 1 0 1... //............ const size_t Plength = ((size_t(h) + 1) * (size_t(w) + 1)) / 4 + 1; //Array used to store info and labeled pixel by each thread. //Different threads affect different memory location of chunksSizeAndLabels int *chunksSizeAndLabels = (int *)cv::fastMalloc(h * sizeof(int)); //Tree of labels LabelT *P = (LabelT *)cv::fastMalloc(Plength * sizeof(LabelT)); //First label is for background P[0] = 0; cv::Range range(0, h); //First scan, each thread works with chunk of img.rows/nThreads rows //e.g. 300 rows, 4 threads -> each chunks is composed of 75 rows cv::parallel_for_(range, FirstScan(img, imgLabels, P, chunksSizeAndLabels), nThreads); //merge labels of different chunks mergeLabels(img, imgLabels, P, chunksSizeAndLabels); LabelT nLabels = 1; for (int i = 0; i < h; i = chunksSizeAndLabels[i]){ flattenL(P, i * w / 4 + 1, chunksSizeAndLabels[i + 1], nLabels); } //Array for statistics data StatsOp *SopArray = new StatsOp[h]; sop.init(nLabels); //Second scan cv::parallel_for_(range, SecondScan(img, imgLabels, P, sop, SopArray, nLabels), nThreads); StatsOp::mergeStats(imgLabels, SopArray, sop, nLabels); sop.finish(); delete[] SopArray; cv::fastFree(chunksSizeAndLabels); cv::fastFree(P); return nLabels; } };//End struct LabelingGranaParallel // Based on “Optimized Block-based Connected Components Labeling with Decision Trees”, Costantino Grana et al // Only for 8-connectivity template struct LabelingGrana{ LabelT operator()(const cv::Mat &img, cv::Mat &imgLabels, int connectivity, StatsOp &sop){ CV_Assert(img.rows == imgLabels.rows); CV_Assert(img.cols == imgLabels.cols); CV_Assert(connectivity == 8); const int h = img.rows; const int w = img.cols; //A quick and dirty upper bound for the maximimum number of labels. //Following formula comes from the fact that a 2x2 block in 8-connectivity case //can never have more than 1 new label and 1 label for background. //Worst case image example pattern: //1 0 1 0 1... //0 0 0 0 0... //1 0 1 0 1... //............ const size_t Plength = ((size_t(h) + 1) * (size_t(w) + 1)) / 4 + 1; LabelT *P = (LabelT *)fastMalloc(sizeof(LabelT)* Plength); P[0] = 0; LabelT lunique = 1; // First scan for (int r = 0; r < h; r += 2) { // Get rows pointer const PixelT * const img_row = img.ptr(r); const PixelT * const img_row_prev = (PixelT *)(((char *)img_row) - img.step.p[0]); const PixelT * const img_row_prev_prev = (PixelT *)(((char *)img_row_prev) - img.step.p[0]); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + img.step.p[0]); LabelT * const imgLabels_row = imgLabels.ptr(r); LabelT * const imgLabels_row_prev_prev = (LabelT *)(((char *)imgLabels_row) - imgLabels.step.p[0] - imgLabels.step.p[0]); for (int c = 0; c < w; c += 2) { // We work with 2x2 blocks // +-+-+-+ // |P|Q|R| // +-+-+-+ // |S|X| // +-+-+ // The pixels are named as follows // +---+---+---+ // |a b|c d|e f| // |g h|i j|k l| // +---+---+---+ // |m n|o p| // |q r|s t| // +---+---+ // Pixels a, f, l, q are not needed, since we need to understand the // the connectivity between these blocks and those pixels only metter // when considering the outer connectivities // A bunch of defines used to check if the pixels are foreground, // without going outside the image limits. #define condition_b c-1>=0 && r-2>=0 && img_row_prev_prev[c-1]>0 #define condition_c r-2>=0 && img_row_prev_prev[c]>0 #define condition_d c+1=0 && img_row_prev_prev[c+1]>0 #define condition_e c+2=0 && img_row_prev_prev[c+2]>0 #define condition_g c-2>=0 && r-1>=0 && img_row_prev[c-2]>0 #define condition_h c-1>=0 && r-1>=0 && img_row_prev[c-1]>0 #define condition_i r-1>=0 && img_row_prev[c]>0 #define condition_j c+1=0 && img_row_prev[c+1]>0 #define condition_k c+2=0 && img_row_prev[c+2]>0 #define condition_m c-2>=0 && img_row[c-2]>0 #define condition_n c-1>=0 && img_row[c-1]>0 #define condition_o img_row[c]>0 #define condition_p c+10 #define condition_r c-1>=0 && r+10 #define condition_s r+10 #define condition_t c+10 // This is a decision tree which allows to choose which action to // perform, checking as few conditions as possible. // Actions: the blocks label are provisionally stored in the top left // pixel of the block in the labels image if (condition_o) { if (condition_n) { if (condition_j) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { if (condition_h) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { if (condition_p) { if (condition_k) { if (condition_d) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { if (condition_h) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } } else { if (condition_r) { if (condition_j) { if (condition_m) { if (condition_h) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { if (condition_g) { if (condition_b) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { if (condition_i) { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } else { if (condition_h) { if (condition_c) { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } else { //Action_14: Merge labels of block P, Q and S imgLabels_row[c] = set_union(P, set_union(P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c]), imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } } else { if (condition_p) { if (condition_k) { if (condition_m) { if (condition_h) { if (condition_d) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { if (condition_d) { if (condition_g) { if (condition_b) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { if (condition_i) { if (condition_g) { if (condition_b) { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(P, set_union(P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(P, set_union(P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } } else { if (condition_i) { if (condition_d) { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(P, set_union(P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { if (condition_h) { if (condition_d) { if (condition_c) { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } else { //Action_15: Merge labels of block P, R and S imgLabels_row[c] = set_union(P, set_union(P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_15: Merge labels of block P, R and S imgLabels_row[c] = set_union(P, set_union(P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } } else { if (condition_h) { if (condition_m) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { // ACTION_9 Merge labels of block P and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c - 2], imgLabels_row[c - 2]); continue; } } else { if (condition_i) { if (condition_m) { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } } } else { if (condition_h) { if (condition_m) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { // ACTION_9 Merge labels of block P and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c - 2], imgLabels_row[c - 2]); continue; } } else { if (condition_i) { if (condition_m) { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } } } } else { if (condition_j) { if (condition_i) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { if (condition_h) { if (condition_c) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { //Action_7: Merge labels of block P and Q imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c]); continue; } } else { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } } } else { if (condition_p) { if (condition_k) { if (condition_i) { if (condition_d) { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } else { // ACTION_10 Merge labels of block Q and R imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]); continue; } } else { if (condition_h) { if (condition_d) { if (condition_c) { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } else { //Action_8: Merge labels of block P and R imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c + 2]); continue; } } else { //Action_8: Merge labels of block P and R imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c - 2], imgLabels_row_prev_prev[c + 2]); continue; } } else { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } } } else { if (condition_i) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { if (condition_h) { //Action_3: Assign label of block P imgLabels_row[c] = imgLabels_row_prev_prev[c - 2]; continue; } else { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = lunique; P[lunique] = lunique; lunique = lunique + 1; continue; } } } } else { if (condition_i) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { if (condition_h) { //Action_3: Assign label of block P imgLabels_row[c] = imgLabels_row_prev_prev[c - 2]; continue; } else { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = lunique; P[lunique] = lunique; lunique = lunique + 1; continue; } } } } } } } else { if (condition_s) { if (condition_p) { if (condition_n) { if (condition_j) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { if (condition_h) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { if (condition_k) { if (condition_d) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { if (condition_h) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } } else { if (condition_r) { if (condition_j) { if (condition_m) { if (condition_h) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { if (condition_g) { if (condition_b) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { if (condition_k) { if (condition_d) { if (condition_m) { if (condition_h) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { if (condition_g) { if (condition_b) { if (condition_i) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_c) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } else { if (condition_i) { if (condition_m) { if (condition_h) { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } else { if (condition_g) { if (condition_b) { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(P, set_union(P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(P, set_union(P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } } else { //Action_16: labels of block Q, R and S imgLabels_row[c] = set_union(P, set_union(P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]), imgLabels_row[c - 2]); continue; } } else { //Action_12: Merge labels of block R and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c + 2], imgLabels_row[c - 2]); continue; } } } else { if (condition_i) { if (condition_m) { if (condition_h) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_g) { if (condition_b) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } } else { //Action_11: Merge labels of block Q and S imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row[c - 2]); continue; } } else { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } } } } else { if (condition_j) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { if (condition_k) { if (condition_i) { if (condition_d) { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } else { // ACTION_10 Merge labels of block Q and R imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]); continue; } } else { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } } else { if (condition_i) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = lunique; P[lunique] = lunique; lunique = lunique + 1; continue; } } } } } } else { if (condition_r) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { if (condition_n) { //Action_6: Assign label of block S imgLabels_row[c] = imgLabels_row[c - 2]; continue; } else { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = lunique; P[lunique] = lunique; lunique = lunique + 1; continue; } } } } else { if (condition_p) { if (condition_j) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { if (condition_k) { if (condition_i) { if (condition_d) { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } else { // ACTION_10 Merge labels of block Q and R imgLabels_row[c] = set_union(P, imgLabels_row_prev_prev[c], imgLabels_row_prev_prev[c + 2]); continue; } } else { //Action_5: Assign label of block R imgLabels_row[c] = imgLabels_row_prev_prev[c + 2]; continue; } } else { if (condition_i) { //Action_4: Assign label of block Q imgLabels_row[c] = imgLabels_row_prev_prev[c]; continue; } else { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = lunique; P[lunique] = lunique; lunique = lunique + 1; continue; } } } } else { if (condition_t) { //Action_2: New label (the block has foreground pixels and is not connected to anything else) imgLabels_row[c] = lunique; P[lunique] = lunique; lunique = lunique + 1; continue; } else { // Action_1: No action (the block has no foreground pixels) imgLabels_row[c] = 0; continue; } } } } } } // Second scan + analysis LabelT nLabels = flattenL(P, lunique); sop.init(nLabels); if (imgLabels.rows & 1){ if (imgLabels.cols & 1){ //Case 1: both rows and cols odd for (int r = 0; r < imgLabels.rows; r += 2) { // Get rows pointer const PixelT * const img_row = img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + img.step.p[0]); LabelT * const imgLabels_row = imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + imgLabels.step.p[0]); for (int c = 0; c < imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; sop(r, c, iLabel); } else{ imgLabels_row[c] = 0; sop(r, c, 0); } if (c + 1 < imgLabels.cols) { if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; sop(r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; sop(r, c + 1, 0); } if (r + 1 < imgLabels.rows) { if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; sop(r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; sop(r + 1, c, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; sop(r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; sop(r + 1, c + 1, 0); } } } else if (r + 1 < imgLabels.rows) { if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; sop(r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; sop(r + 1, c, 0); } } } else { imgLabels_row[c] = 0; sop(r, c, 0); if (c + 1 < imgLabels.cols) { imgLabels_row[c + 1] = 0; sop(r, c + 1, 0); if (r + 1 < imgLabels.rows) { imgLabels_row_fol[c] = 0; imgLabels_row_fol[c + 1] = 0; sop(r + 1, c, 0); sop(r + 1, c + 1, 0); } } else if (r + 1 < imgLabels.rows) { imgLabels_row_fol[c] = 0; sop(r + 1, c, 0); } } } } }//END Case 1 else{ //Case 2: only rows odd for (int r = 0; r < imgLabels.rows; r += 2) { // Get rows pointer const PixelT * const img_row = img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + img.step.p[0]); LabelT * const imgLabels_row = imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + imgLabels.step.p[0]); for (int c = 0; c < imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; sop(r, c, iLabel); } else{ imgLabels_row[c] = 0; sop(r, c, 0); } if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; sop(r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; sop(r, c + 1, 0); } if (r + 1 < imgLabels.rows) { if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; sop(r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; sop(r + 1, c, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; sop(r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; sop(r + 1, c + 1, 0); } } } else { imgLabels_row[c] = 0; imgLabels_row[c + 1] = 0; sop(r, c, 0); sop(r, c + 1, 0); if (r + 1 < imgLabels.rows) { imgLabels_row_fol[c] = 0; imgLabels_row_fol[c + 1] = 0; sop(r + 1, c, 0); sop(r + 1, c + 1, 0); } } } } }// END Case 2 } else{ if (imgLabels.cols & 1){ //Case 3: only cols odd for (int r = 0; r < imgLabels.rows; r += 2) { // Get rows pointer const PixelT * const img_row = img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + img.step.p[0]); LabelT * const imgLabels_row = imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + imgLabels.step.p[0]); for (int c = 0; c < imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; sop(r, c, iLabel); } else{ imgLabels_row[c] = 0; sop(r, c, 0); } if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; sop(r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; sop(r + 1, c, 0); } if (c + 1 < imgLabels.cols) { if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; sop(r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; sop(r, c + 1, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; sop(r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; sop(r + 1, c + 1, 0); } } } else{ imgLabels_row[c] = 0; imgLabels_row_fol[c] = 0; sop(r, c, 0); sop(r + 1, c, 0); if (c + 1 < imgLabels.cols) { imgLabels_row[c + 1] = 0; imgLabels_row_fol[c + 1] = 0; sop(r, c + 1, 0); sop(r + 1, c + 1, 0); } } } } }// END case 3 else{ //Case 4: nothing odd for (int r = 0; r < imgLabels.rows; r += 2) { // Get rows pointer const PixelT * const img_row = img.ptr(r); const PixelT * const img_row_fol = (PixelT *)(((char *)img_row) + img.step.p[0]); LabelT * const imgLabels_row = imgLabels.ptr(r); LabelT * const imgLabels_row_fol = (LabelT *)(((char *)imgLabels_row) + imgLabels.step.p[0]); for (int c = 0; c < imgLabels.cols; c += 2) { LabelT iLabel = imgLabels_row[c]; if (iLabel > 0) { iLabel = P[iLabel]; if (img_row[c] > 0){ imgLabels_row[c] = iLabel; sop(r, c, iLabel); } else{ imgLabels_row[c] = 0; sop(r, c, 0); } if (img_row[c + 1] > 0){ imgLabels_row[c + 1] = iLabel; sop(r, c + 1, iLabel); } else{ imgLabels_row[c + 1] = 0; sop(r, c + 1, 0); } if (img_row_fol[c] > 0){ imgLabels_row_fol[c] = iLabel; sop(r + 1, c, iLabel); } else{ imgLabels_row_fol[c] = 0; sop(r + 1, c, 0); } if (img_row_fol[c + 1] > 0){ imgLabels_row_fol[c + 1] = iLabel; sop(r + 1, c + 1, iLabel); } else{ imgLabels_row_fol[c + 1] = 0; sop(r + 1, c + 1, 0); } } else { imgLabels_row[c] = 0; imgLabels_row[c + 1] = 0; imgLabels_row_fol[c] = 0; imgLabels_row_fol[c + 1] = 0; sop(r, c, 0); sop(r, c + 1, 0); sop(r + 1, c, 0); sop(r + 1, c + 1, 0); } } } }//END case 4 } sop.finish(); fastFree(P); return nLabels; } //End function LabelingGrana operator() };//End struct LabelingGrana }//end namespace connectedcomponents //L's type must have an appropriate depth for the number of pixels in I template static int connectedComponents_sub1(const cv::Mat &I, cv::Mat &L, int connectivity, int ccltype, StatsOp &sop){ CV_Assert(L.channels() == 1 && I.channels() == 1); CV_Assert(connectivity == 8 || connectivity == 4); CV_Assert(ccltype == CCL_GRANA || ccltype == CCL_WU || ccltype == CCL_DEFAULT); int lDepth = L.depth(); int iDepth = I.depth(); const char* currentParallelFramework = cv::currentParallelFramework(); CV_Assert(iDepth == CV_8U || iDepth == CV_8S); if (ccltype == CCL_WU || connectivity == 4){ // Wu algorithm is used using connectedcomponents::LabelingWu; using connectedcomponents::LabelingWuParallel; //warn if L's depth is not sufficient? if (lDepth == CV_8U){ if (currentParallelFramework == NULL) return (int)LabelingWu()(I, L, connectivity, sop); else return (int)LabelingWuParallel()(I, L, connectivity, sop); } else if (lDepth == CV_16U){ if (currentParallelFramework == NULL) return (int)LabelingWu()(I, L, connectivity, sop); else return (int)LabelingWuParallel()(I, L, connectivity, sop); } else if (lDepth == CV_32S){ //note that signed types don't really make sense here and not being able to use unsigned matters for scientific projects //OpenCV: how should we proceed? .at typechecks in debug mode if (currentParallelFramework == NULL) return (int)LabelingWu()(I, L, connectivity, sop); else return (int)LabelingWuParallel()(I, L, connectivity, sop); } } else if ((ccltype == CCL_GRANA || ccltype == CCL_DEFAULT) && connectivity == 8){ // Grana algorithm is used using connectedcomponents::LabelingGrana; using connectedcomponents::LabelingGranaParallel; //warn if L's depth is not sufficient? if (lDepth == CV_8U){ if (currentParallelFramework == NULL) return (int)LabelingGrana()(I, L, connectivity, sop); else return (int)LabelingGranaParallel()(I, L, connectivity, sop); } else if (lDepth == CV_16U){ if (currentParallelFramework == NULL) return (int)LabelingGrana()(I, L, connectivity, sop); else return (int)LabelingGranaParallel()(I, L, connectivity, sop); } else if (lDepth == CV_32S){ //note that signed types don't really make sense here and not being able to use unsigned matters for scientific projects //OpenCV: how should we proceed? .at typechecks in debug mode if (currentParallelFramework == NULL) return (int)LabelingGrana()(I, L, connectivity, sop); else return (int)LabelingGranaParallel()(I, L, connectivity, sop); } } CV_Error(CV_StsUnsupportedFormat, "unsupported label/image type"); return -1; } } // Simple wrapper to ensure binary and source compatibility (ABI) int cv::connectedComponents(InputArray _img, OutputArray _labels, int connectivity, int ltype){ return cv::connectedComponents(_img, _labels, connectivity, ltype, CCL_DEFAULT); } int cv::connectedComponents(InputArray _img, OutputArray _labels, int connectivity, int ltype, int ccltype){ const cv::Mat img = _img.getMat(); _labels.create(img.size(), CV_MAT_DEPTH(ltype)); cv::Mat labels = _labels.getMat(); connectedcomponents::NoOp sop; if (ltype == CV_16U){ return connectedComponents_sub1(img, labels, connectivity, ccltype, sop); } else if (ltype == CV_32S){ return connectedComponents_sub1(img, labels, connectivity, ccltype, sop); } else{ CV_Error(CV_StsUnsupportedFormat, "the type of labels must be 16u or 32s"); return 0; } } // Simple wrapper to ensure binary and source compatibility (ABI) int cv::connectedComponentsWithStats(InputArray _img, OutputArray _labels, OutputArray statsv, OutputArray centroids, int connectivity, int ltype) { return cv::connectedComponentsWithStats(_img, _labels, statsv, centroids, connectivity, ltype, CCL_DEFAULT); } int cv::connectedComponentsWithStats(InputArray _img, OutputArray _labels, OutputArray statsv, OutputArray centroids, int connectivity, int ltype, int ccltype) { const cv::Mat img = _img.getMat(); _labels.create(img.size(), CV_MAT_DEPTH(ltype)); cv::Mat labels = _labels.getMat(); connectedcomponents::CCStatsOp sop(statsv, centroids); if (ltype == CV_16U){ return connectedComponents_sub1(img, labels, connectivity, ccltype, sop); } else if (ltype == CV_32S){ return connectedComponents_sub1(img, labels, connectivity, ccltype, sop); } else{ CV_Error(CV_StsUnsupportedFormat, "the type of labels must be 16u or 32s"); return 0; } }