/*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 //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 LabelingImpl{ 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 LabelingImpl operator() };//End struct LabelingImpl }//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, StatsOp &sop){ CV_Assert(L.channels() == 1 && I.channels() == 1); CV_Assert(connectivity == 8 || connectivity == 4); int lDepth = L.depth(); int iDepth = I.depth(); using connectedcomponents::LabelingImpl; //warn if L's depth is not sufficient? CV_Assert(iDepth == CV_8U || iDepth == CV_8S); if(lDepth == CV_8U){ return (int) LabelingImpl()(I, L, connectivity, sop); }else if(lDepth == CV_16U){ return (int) LabelingImpl()(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) LabelingImpl()(I, L, connectivity, sop); } CV_Error(CV_StsUnsupportedFormat, "unsupported label/image type"); return -1; } } int cv::connectedComponents(InputArray _img, OutputArray _labels, int connectivity, int ltype){ 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, sop); }else if(ltype == CV_32S){ return connectedComponents_sub1(img, labels, connectivity, sop); }else{ CV_Error(CV_StsUnsupportedFormat, "the type of labels must be 16u or 32s"); return 0; } } int cv::connectedComponentsWithStats(InputArray _img, OutputArray _labels, OutputArray statsv, OutputArray centroids, int connectivity, int ltype) { 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, sop); }else if(ltype == CV_32S){ return connectedComponents_sub1(img, labels, connectivity, sop); }else{ CV_Error(CV_StsUnsupportedFormat, "the type of labels must be 16u or 32s"); return 0; } }