/*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 //M*/ // #include "precomp.hpp" #include namespace cv{ namespace connectedcomponents{ struct NoOp{ NoOp(){ } void init(int /*labels*/){ } inline void operator()(int r, int c, int l){ (void) r; (void) c; (void) l; } void finish(){} }; 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; 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)); } 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; } } }; //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; } //Based on "Two Strategies to Speed up Connected Components Algorithms", the SAUF (Scan array union find) variant //using decision trees //Kesheng Wu, et al //Note: rows are encoded as position in the "rows" array to save lookup times //reference for 4-way: {{-1, 0}, {0, -1}};//b, d neighborhoods const int G4[2][2] = {{1, 0}, {0, -1}};//b, d neighborhoods //reference for 8-way: {{-1, -1}, {-1, 0}, {-1, 1}, {0, -1}};//a, b, c, d neighborhoods const int G8[4][2] = {{1, -1}, {1, 0}, {1, 1}, {0, -1}};//a, b, c, d neighborhoods template struct LabelingWu{ LabelT operator()(const cv::Mat &I, cv::Mat &L, int connectivity, StatsOp &sop){ CV_Assert(L.rows == I.rows); CV_Assert(L.cols == I.cols); CV_Assert(connectivity == 8 || connectivity == 4); const int rows = L.rows; const int cols = L.cols; //A quick and dirty upper bound for the maximimum number of labels. The 4 comes from //the fact that a 3x3 block can never have more than 4 unique labels for both 4 & 8-way const size_t Plength = 4 * (size_t(rows + 3 - 1)/3) * (size_t(cols + 3 - 1)/3); LabelT *P = (LabelT *) fastMalloc(sizeof(LabelT) * Plength); P[0] = 0; LabelT lunique = 1; //scanning phase for(int r_i = 0; r_i < rows; ++r_i){ LabelT * const Lrow = L.ptr(r_i); LabelT * const Lrow_prev = (LabelT *)(((char *)Lrow) - L.step.p[0]); const PixelT * const Irow = I.ptr(r_i); const PixelT * const Irow_prev = (const PixelT *)(((char *)Irow) - I.step.p[0]); LabelT *Lrows[2] = { Lrow, Lrow_prev }; const PixelT *Irows[2] = { Irow, Irow_prev }; if(connectivity == 8){ const int a = 0; const int b = 1; const int c = 2; const int d = 3; const bool T_a_r = (r_i - G8[a][0]) >= 0; const bool T_b_r = (r_i - G8[b][0]) >= 0; const bool T_c_r = (r_i - G8[c][0]) >= 0; for(int c_i = 0; Irows[0] != Irow + cols; ++Irows[0], c_i++){ if(!*Irows[0]){ Lrow[c_i] = 0; continue; } Irows[1] = Irow_prev + c_i; Lrows[0] = Lrow + c_i; Lrows[1] = Lrow_prev + c_i; const bool T_a = T_a_r && (c_i + G8[a][1]) >= 0 && *(Irows[G8[a][0]] + G8[a][1]); const bool T_b = T_b_r && *(Irows[G8[b][0]] + G8[b][1]); const bool T_c = T_c_r && (c_i + G8[c][1]) < cols && *(Irows[G8[c][0]] + G8[c][1]); const bool T_d = (c_i + G8[d][1]) >= 0 && *(Irows[G8[d][0]] + G8[d][1]); //decision tree if(T_b){ //copy(b) *Lrows[0] = *(Lrows[G8[b][0]] + G8[b][1]); }else{//not b if(T_c){ if(T_a){ //copy(c, a) *Lrows[0] = set_union(P, *(Lrows[G8[c][0]] + G8[c][1]), *(Lrows[G8[a][0]] + G8[a][1])); }else{ if(T_d){ //copy(c, d) *Lrows[0] = set_union(P, *(Lrows[G8[c][0]] + G8[c][1]), *(Lrows[G8[d][0]] + G8[d][1])); }else{ //copy(c) *Lrows[0] = *(Lrows[G8[c][0]] + G8[c][1]); } } }else{//not c if(T_a){ //copy(a) *Lrows[0] = *(Lrows[G8[a][0]] + G8[a][1]); }else{ if(T_d){ //copy(d) *Lrows[0] = *(Lrows[G8[d][0]] + G8[d][1]); }else{ //new label *Lrows[0] = lunique; P[lunique] = lunique; lunique = lunique + 1; } } } } } }else{ //B & D only const int b = 0; const int d = 1; const bool T_b_r = (r_i - G4[b][0]) >= 0; for(int c_i = 0; Irows[0] != Irow + cols; ++Irows[0], c_i++){ if(!*Irows[0]){ Lrow[c_i] = 0; continue; } Irows[1] = Irow_prev + c_i; Lrows[0] = Lrow + c_i; Lrows[1] = Lrow_prev + c_i; const bool T_b = T_b_r && *(Irows[G4[b][0]] + G4[b][1]); const bool T_d = (c_i + G4[d][1]) >= 0 && *(Irows[G4[d][0]] + G4[d][1]); if(T_b){ if(T_d){ //copy(d, b) *Lrows[0] = set_union(P, *(Lrows[G4[d][0]] + G4[d][1]), *(Lrows[G4[b][0]] + G4[b][1])); }else{ //copy(b) *Lrows[0] = *(Lrows[G4[b][0]] + G4[b][1]); } }else{ if(T_d){ //copy(d) *Lrows[0] = *(Lrows[G4[d][0]] + G4[d][1]); }else{ //new label *Lrows[0] = lunique; P[lunique] = lunique; lunique = lunique + 1; } } } } } //analysis LabelT nLabels = flattenL(P, lunique); sop.init(nLabels); for(int r_i = 0; r_i < rows; ++r_i){ LabelT *Lrow_start = L.ptr(r_i); LabelT *Lrow_end = Lrow_start + cols; LabelT *Lrow = Lrow_start; for(int c_i = 0; Lrow != Lrow_end; ++Lrow, ++c_i){ const LabelT l = P[*Lrow]; *Lrow = l; sop(r_i, c_i, l); } } 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 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 || connectivity == 4); const int h = img.rows; const int w = img.cols; //A quick and dirty upper bound for the maximimum number of labels. const size_t Plength = img.rows*img.cols / 4; LabelT *P = (LabelT *)fastMalloc(sizeof(LabelT)* Plength); P[0] = 0; LabelT lunique = 1; // First scan for (int r = 0; r(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(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; c0) { 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 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 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 + 10){ 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(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; c0) { 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 + 10){ 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(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; c0) { 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 + 10){ 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(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; c0) { 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(); CV_Assert(iDepth == CV_8U || iDepth == CV_8S); if (ccltype == CCL_WU || connectivity == 4){ // Wu algorithm is used using connectedcomponents::LabelingWu; //warn if L's depth is not sufficient? if (lDepth == CV_8U){ return (int)LabelingWu()(I, L, connectivity, sop); } else if (lDepth == CV_16U){ return (int)LabelingWu()(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 return (int)LabelingWu()(I, L, connectivity, sop); } }else if ((ccltype == CCL_GRANA || ccltype == CCL_DEFAULT) && connectivity == 8){ // Grana algorithm is used using connectedcomponents::LabelingGrana; //warn if L's depth is not sufficient? if (lDepth == CV_8U){ return (int)LabelingGrana()(I, L, connectivity, sop); } else if (lDepth == CV_16U){ return (int)LabelingGrana()(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 return (int)LabelingGrana()(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; } }