/*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 //It's 2012 and we still let compilers get by without defining standard integer types... typedef schar int8_t; typedef uchar uint8_t; typedef short int16_t; typedef unsigned short uint16_t; typedef int int32_t; typedef unsigned int uint32_t; namespace cv{ namespace connectedcomponents{ template struct NoOp{ NoOp(){ } void init(const LabelT labels){ (void) labels; } inline void operator()(int r, int c, LabelT l){ (void) r; (void) c; (void) l; } void finish(){} }; template struct CCStatsOp{ std::vector &statsv; CCStatsOp(std::vector &_statsv): statsv(_statsv){ } inline void init(const LabelT nlabels){ statsv.clear(); cv::ConnectedComponentStats stats = cv::ConnectedComponentStats(); stats.lower_x = std::numeric_limits::max(); stats.lower_y = std::numeric_limits::max(); stats.upper_x = std::numeric_limits::min(); stats.upper_y = std::numeric_limits::min(); stats.centroid_x = 0; stats.centroid_y = 0; stats.integral_x = 0; stats.integral_y = 0; stats.area = 0; statsv.resize(nlabels, stats); } void operator()(int r, int c, LabelT l){ ConnectedComponentStats &stats = statsv[l]; if(c > stats.upper_x){ stats.upper_x = c; }else{ if(c < stats.lower_x){ stats.lower_x = c; } } if(r > stats.upper_y){ stats.upper_y = r; }else{ if(r < stats.lower_y){ stats.lower_y = r; } } stats.integral_x += c; stats.integral_y += r; stats.area++; } void finish(){ for(size_t l = 0; l < statsv.size(); ++l){ ConnectedComponentStats &stats = statsv[l]; stats.lower_x = std::min(stats.lower_x, stats.upper_x); stats.lower_y = std::min(stats.lower_y, stats.upper_y); stats.centroid_x = stats.integral_x / double(stats.area); stats.centroid_y = stats.integral_y / double(stats.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, int connectivity = 8> struct LabelingImpl{ LabelT operator()(Mat &L, const Mat &I, StatsOp &sop){ const int rows = L.rows; const int cols = L.cols; size_t Plength = (size_t(rows + 3 - 1)/3) * (size_t(cols + 3 - 1)/3); if(connectivity == 4){ Plength = 4 * Plength;//a quick and dirty upper bound, an exact answer exists if you want to find it //the 4 comes from the fact that a 3x3 block can never have more than 4 unique labels } 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 *Lrow = (LabelT *)(L.data + L.step.p[0] * r_i); LabelT *Lrow_prev = (LabelT *)(((char *)Lrow) - L.step.p[0]); const PixelT *Irow = (PixelT *)(I.data + I.step.p[0] * r_i); const PixelT *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 assert(connectivity == 4); 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 = (LabelT *)(L.data + L.step.p[0] * 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 int connectedComponents_sub1(Mat &L, const Mat &I, int connectivity, StatsOp &sop){ CV_Assert(L.rows == I.rows); CV_Assert(L.cols == I.cols); 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? if(lDepth == CV_8U){ if(iDepth == CV_8U || iDepth == CV_8S){ if(connectivity == 4){ return (int) LabelingImpl()(L, I, sop); }else{ return (int) LabelingImpl()(L, I, sop); } }else{ CV_Assert(false); } }else if(lDepth == CV_16U){ if(iDepth == CV_8U || iDepth == CV_8S){ if(connectivity == 4){ return (int) LabelingImpl()(L, I, sop); }else{ return (int) LabelingImpl()(L, I, sop); } }else{ CV_Assert(false); } }else if(lDepth == CV_32S){ //note that signed types don't really make sense here and not being able to use uint32_t matters for scientific projects //OpenCV: how should we proceed? .at typechecks in debug mode if(iDepth == CV_8U || iDepth == CV_8S){ if(connectivity == 4){ return (int) LabelingImpl()(L, I, sop); }else{ return (int) LabelingImpl()(L, I, sop); } }else{ CV_Assert(false); } } CV_Error(CV_StsUnsupportedFormat, "unsupported label/image type"); return -1; } int connectedComponents(Mat &L, const Mat &I, int connectivity){ int lDepth = L.depth(); if(lDepth == CV_8U){ connectedcomponents::NoOp sop; return connectedComponents_sub1(L, I, connectivity, sop); }else if(lDepth == CV_16U){ connectedcomponents::NoOp sop; return connectedComponents_sub1(L, I, connectivity, sop); }else if(lDepth == CV_32S){ connectedcomponents::NoOp sop; return connectedComponents_sub1(L, I, connectivity, sop); }else{ CV_Assert(false); return 0; } } int connectedComponentsWithStats(Mat &L, const Mat &I, std::vector &statsv, int connectivity){ int lDepth = L.depth(); if(lDepth == CV_8U){ connectedcomponents::CCStatsOp sop(statsv); return connectedComponents_sub1(L, I, connectivity, sop); }else if(lDepth == CV_16U){ connectedcomponents::CCStatsOp sop(statsv); return connectedComponents_sub1(L, I, connectivity, sop); }else if(lDepth == CV_32S){ connectedcomponents::CCStatsOp sop(statsv); return connectedComponents_sub1(L, I, connectivity, sop); }else{ CV_Assert(false); return 0; } } }