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opencv/modules/imgproc/src/connectedcomponents.cpp
Vadim Pisarevsky 5ddd25313f Add Grana's connected components algorithm for 8-way connectivity. (#6823) 
* Add Grana's connected components algorithm for 8-way connectivity. That algorithm is faster than Wu's one (currently implemented in opencv). For more details see https://github.com/prittt/YACCLAB.

* New functions signature and distance transform compatibility

* Add tests to imgproc/test/test_connectedcomponents.cpp

* Change of test_connectedcomponents.cpp for c++98 support
2016-08-26 16:01:00 +04:00

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
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// 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 <nevion@gmail.com>
// 2016 Costantino Grama <costantino.grana@unimore.it>
// 2016 Federico Bolelli <federico.bolelli@hotmail.com>
// 2016 Lorenzo Baraldi <lorenzo.baraldi@unimore.it>
// 2016 Roberto Vezzani <roberto.vezzani@unimore.it>
//M*/
//
#include "precomp.hpp"
#include <vector>
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<Point2ui64> 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<int>::type);
statsv = _mstatsv->getMat();
_mcentroidsv->create(cv::Size(2, nlabels), cv::DataType<double>::type);
centroidsv = _mcentroidsv->getMat();
for(int l = 0; l < (int) nlabels; ++l){
int *row = (int *) &statsv.at<int>(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<int>(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<int>(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 = &centroidsv.at<double>(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<typename LabelT>
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<typename LabelT>
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<typename LabelT>
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<typename LabelT>
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<typename LabelT>
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<typename LabelT, typename PixelT, typename StatsOp = NoOp >
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<LabelT>(r_i);
LabelT * const Lrow_prev = (LabelT *)(((char *)Lrow) - L.step.p[0]);
const PixelT * const Irow = I.ptr<PixelT>(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<LabelT>(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 <20>Optimized Block-based Connected Components Labeling with Decision Trees<65>, Costantino Grana et al
// Only for 8-connectivity
template<typename LabelT, typename PixelT, typename StatsOp = NoOp >
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<h; r += 2) {
// Get rows pointer
const PixelT* const img_row = img.ptr<PixelT>(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<LabelT>(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<w && r-2>=0 && img_row_prev_prev[c+1]>0
#define condition_e c+2<w && r-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<w && r-1>=0 && img_row_prev[c+1]>0
#define condition_k c+2<w && r-1>=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+1<w && img_row[c+1]>0
#define condition_r c-1>=0 && r+1<h && img_row_fol[c-1]>0
#define condition_s r+1<h && img_row_fol[c]>0
#define condition_t c+1<w && r+1<h && img_row_fol[c+1]>0
// 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<PixelT>(r);
const PixelT* const img_row_fol = (PixelT *)(((char *)img_row) + img.step.p[0]);
LabelT* const imgLabels_row = imgLabels.ptr<LabelT>(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<PixelT>(r);
const PixelT* const img_row_fol = (PixelT *)(((char *)img_row) + img.step.p[0]);
LabelT* const imgLabels_row = imgLabels.ptr<LabelT>(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<PixelT>(r);
const PixelT* const img_row_fol = (PixelT *)(((char *)img_row) + img.step.p[0]);
LabelT* const imgLabels_row = imgLabels.ptr<LabelT>(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<PixelT>(r);
const PixelT* const img_row_fol = (PixelT *)(((char *)img_row) + img.step.p[0]);
LabelT* const imgLabels_row = imgLabels.ptr<LabelT>(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<typename StatsOp>
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<uchar, uchar, StatsOp>()(I, L, connectivity, sop);
}
else if (lDepth == CV_16U){
return (int)LabelingWu<ushort, uchar, StatsOp>()(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<T> typechecks in debug mode
return (int)LabelingWu<int, uchar, StatsOp>()(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<uchar, uchar, StatsOp>()(I, L, connectivity, sop);
}
else if (lDepth == CV_16U){
return (int)LabelingGrana<ushort, uchar, StatsOp>()(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<T> typechecks in debug mode
return (int)LabelingGrana<int, uchar, StatsOp>()(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;
}
}
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