/*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. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000, Intel Corporation, all rights reserved. // Copyright (C) 2013, OpenCV Foundation, 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 the copyright holders 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. // //M*/ #include "precomp.hpp" namespace cv { static const int DIST_SHIFT = 16; static const int INIT_DIST0 = (INT_MAX >> 2); #define CV_FLT_TO_FIX(x,n) cvRound((x)*(1<<(n))) static void initTopBottom( Mat& temp, int border ) { Size size = temp.size(); for( int i = 0; i < border; i++ ) { int* ttop = temp.ptr(i); int* tbottom = temp.ptr(size.height - i - 1); for( int j = 0; j < size.width; j++ ) { ttop[j] = INIT_DIST0; tbottom[j] = INIT_DIST0; } } } static void distanceTransform_3x3( const Mat& _src, Mat& _temp, Mat& _dist, const float* metrics ) { const int BORDER = 1; int i, j; const int HV_DIST = CV_FLT_TO_FIX( metrics[0], DIST_SHIFT ); const int DIAG_DIST = CV_FLT_TO_FIX( metrics[1], DIST_SHIFT ); const float scale = 1.f/(1 << DIST_SHIFT); const uchar* src = _src.data; int* temp = _temp.ptr(); float* dist = _dist.ptr(); int srcstep = (int)(_src.step/sizeof(src[0])); int step = (int)(_temp.step/sizeof(temp[0])); int dststep = (int)(_dist.step/sizeof(dist[0])); Size size = _src.size(); initTopBottom( _temp, BORDER ); // forward pass for( i = 0; i < size.height; i++ ) { const uchar* s = src + i*srcstep; int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; for( j = 0; j < BORDER; j++ ) tmp[-j-1] = tmp[size.width + j] = INIT_DIST0; for( j = 0; j < size.width; j++ ) { if( !s[j] ) tmp[j] = 0; else { int t0 = tmp[j-step-1] + DIAG_DIST; int t = tmp[j-step] + HV_DIST; if( t0 > t ) t0 = t; t = tmp[j-step+1] + DIAG_DIST; if( t0 > t ) t0 = t; t = tmp[j-1] + HV_DIST; if( t0 > t ) t0 = t; tmp[j] = t0; } } } // backward pass for( i = size.height - 1; i >= 0; i-- ) { float* d = (float*)(dist + i*dststep); int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; for( j = size.width - 1; j >= 0; j-- ) { int t0 = tmp[j]; if( t0 > HV_DIST ) { int t = tmp[j+step+1] + DIAG_DIST; if( t0 > t ) t0 = t; t = tmp[j+step] + HV_DIST; if( t0 > t ) t0 = t; t = tmp[j+step-1] + DIAG_DIST; if( t0 > t ) t0 = t; t = tmp[j+1] + HV_DIST; if( t0 > t ) t0 = t; tmp[j] = t0; } d[j] = (float)(t0 * scale); } } } static void distanceTransform_5x5( const Mat& _src, Mat& _temp, Mat& _dist, const float* metrics ) { const int BORDER = 2; int i, j; const int HV_DIST = CV_FLT_TO_FIX( metrics[0], DIST_SHIFT ); const int DIAG_DIST = CV_FLT_TO_FIX( metrics[1], DIST_SHIFT ); const int LONG_DIST = CV_FLT_TO_FIX( metrics[2], DIST_SHIFT ); const float scale = 1.f/(1 << DIST_SHIFT); const uchar* src = _src.data; int* temp = _temp.ptr(); float* dist = _dist.ptr(); int srcstep = (int)(_src.step/sizeof(src[0])); int step = (int)(_temp.step/sizeof(temp[0])); int dststep = (int)(_dist.step/sizeof(dist[0])); Size size = _src.size(); initTopBottom( _temp, BORDER ); // forward pass for( i = 0; i < size.height; i++ ) { const uchar* s = src + i*srcstep; int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; for( j = 0; j < BORDER; j++ ) tmp[-j-1] = tmp[size.width + j] = INIT_DIST0; for( j = 0; j < size.width; j++ ) { if( !s[j] ) tmp[j] = 0; else { int t0 = tmp[j-step*2-1] + LONG_DIST; int t = tmp[j-step*2+1] + LONG_DIST; if( t0 > t ) t0 = t; t = tmp[j-step-2] + LONG_DIST; if( t0 > t ) t0 = t; t = tmp[j-step-1] + DIAG_DIST; if( t0 > t ) t0 = t; t = tmp[j-step] + HV_DIST; if( t0 > t ) t0 = t; t = tmp[j-step+1] + DIAG_DIST; if( t0 > t ) t0 = t; t = tmp[j-step+2] + LONG_DIST; if( t0 > t ) t0 = t; t = tmp[j-1] + HV_DIST; if( t0 > t ) t0 = t; tmp[j] = t0; } } } // backward pass for( i = size.height - 1; i >= 0; i-- ) { float* d = (float*)(dist + i*dststep); int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; for( j = size.width - 1; j >= 0; j-- ) { int t0 = tmp[j]; if( t0 > HV_DIST ) { int t = tmp[j+step*2+1] + LONG_DIST; if( t0 > t ) t0 = t; t = tmp[j+step*2-1] + LONG_DIST; if( t0 > t ) t0 = t; t = tmp[j+step+2] + LONG_DIST; if( t0 > t ) t0 = t; t = tmp[j+step+1] + DIAG_DIST; if( t0 > t ) t0 = t; t = tmp[j+step] + HV_DIST; if( t0 > t ) t0 = t; t = tmp[j+step-1] + DIAG_DIST; if( t0 > t ) t0 = t; t = tmp[j+step-2] + LONG_DIST; if( t0 > t ) t0 = t; t = tmp[j+1] + HV_DIST; if( t0 > t ) t0 = t; tmp[j] = t0; } d[j] = (float)(t0 * scale); } } } static void distanceTransformEx_5x5( const Mat& _src, Mat& _temp, Mat& _dist, Mat& _labels, const float* metrics ) { const int BORDER = 2; int i, j; const int HV_DIST = CV_FLT_TO_FIX( metrics[0], DIST_SHIFT ); const int DIAG_DIST = CV_FLT_TO_FIX( metrics[1], DIST_SHIFT ); const int LONG_DIST = CV_FLT_TO_FIX( metrics[2], DIST_SHIFT ); const float scale = 1.f/(1 << DIST_SHIFT); const uchar* src = _src.data; int* temp = _temp.ptr(); float* dist = _dist.ptr(); int* labels = _labels.ptr(); int srcstep = (int)(_src.step/sizeof(src[0])); int step = (int)(_temp.step/sizeof(temp[0])); int dststep = (int)(_dist.step/sizeof(dist[0])); int lstep = (int)(_labels.step/sizeof(dist[0])); Size size = _src.size(); initTopBottom( _temp, BORDER ); // forward pass for( i = 0; i < size.height; i++ ) { const uchar* s = src + i*srcstep; int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; int* lls = (int*)(labels + i*lstep); for( j = 0; j < BORDER; j++ ) tmp[-j-1] = tmp[size.width + j] = INIT_DIST0; for( j = 0; j < size.width; j++ ) { if( !s[j] ) { tmp[j] = 0; //assert( lls[j] != 0 ); } else { int t0 = INIT_DIST0, t; int l0 = 0; t = tmp[j-step*2-1] + LONG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j-lstep*2-1]; } t = tmp[j-step*2+1] + LONG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j-lstep*2+1]; } t = tmp[j-step-2] + LONG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j-lstep-2]; } t = tmp[j-step-1] + DIAG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j-lstep-1]; } t = tmp[j-step] + HV_DIST; if( t0 > t ) { t0 = t; l0 = lls[j-lstep]; } t = tmp[j-step+1] + DIAG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j-lstep+1]; } t = tmp[j-step+2] + LONG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j-lstep+2]; } t = tmp[j-1] + HV_DIST; if( t0 > t ) { t0 = t; l0 = lls[j-1]; } tmp[j] = t0; lls[j] = l0; } } } // backward pass for( i = size.height - 1; i >= 0; i-- ) { float* d = (float*)(dist + i*dststep); int* tmp = (int*)(temp + (i+BORDER)*step) + BORDER; int* lls = (int*)(labels + i*lstep); for( j = size.width - 1; j >= 0; j-- ) { int t0 = tmp[j]; int l0 = lls[j]; if( t0 > HV_DIST ) { int t = tmp[j+step*2+1] + LONG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j+lstep*2+1]; } t = tmp[j+step*2-1] + LONG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j+lstep*2-1]; } t = tmp[j+step+2] + LONG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j+lstep+2]; } t = tmp[j+step+1] + DIAG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j+lstep+1]; } t = tmp[j+step] + HV_DIST; if( t0 > t ) { t0 = t; l0 = lls[j+lstep]; } t = tmp[j+step-1] + DIAG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j+lstep-1]; } t = tmp[j+step-2] + LONG_DIST; if( t0 > t ) { t0 = t; l0 = lls[j+lstep-2]; } t = tmp[j+1] + HV_DIST; if( t0 > t ) { t0 = t; l0 = lls[j+1]; } tmp[j] = t0; lls[j] = l0; } d[j] = (float)(t0 * scale); } } } static void getDistanceTransformMask( int maskType, float *metrics ) { CV_Assert( metrics != 0 ); switch (maskType) { case 30: metrics[0] = 1.0f; metrics[1] = 1.0f; break; case 31: metrics[0] = 1.0f; metrics[1] = 2.0f; break; case 32: metrics[0] = 0.955f; metrics[1] = 1.3693f; break; case 50: metrics[0] = 1.0f; metrics[1] = 1.0f; metrics[2] = 2.0f; break; case 51: metrics[0] = 1.0f; metrics[1] = 2.0f; metrics[2] = 3.0f; break; case 52: metrics[0] = 1.0f; metrics[1] = 1.4f; metrics[2] = 2.1969f; break; default: CV_Error(CV_StsBadArg, "Uknown metric type"); } } struct DTColumnInvoker { DTColumnInvoker( const Mat* _src, Mat* _dst, const int* _sat_tab, const float* _sqr_tab) { src = _src; dst = _dst; sat_tab = _sat_tab + src->rows*2 + 1; sqr_tab = _sqr_tab; } void operator()( const BlockedRange& range ) const { int i, i1 = range.begin(), i2 = range.end(); int m = src->rows; size_t sstep = src->step, dstep = dst->step/sizeof(float); AutoBuffer _d(m); int* d = _d; for( i = i1; i < i2; i++ ) { const uchar* sptr = src->ptr(m-1) + i; float* dptr = dst->ptr() + i; int j, dist = m-1; for( j = m-1; j >= 0; j--, sptr -= sstep ) { dist = (dist + 1) & (sptr[0] == 0 ? 0 : -1); d[j] = dist; } dist = m-1; for( j = 0; j < m; j++, dptr += dstep ) { dist = dist + 1 - sat_tab[dist - d[j]]; d[j] = dist; dptr[0] = sqr_tab[dist]; } } } const Mat* src; Mat* dst; const int* sat_tab; const float* sqr_tab; }; struct DTRowInvoker { DTRowInvoker( Mat* _dst, const float* _sqr_tab, const float* _inv_tab ) { dst = _dst; sqr_tab = _sqr_tab; inv_tab = _inv_tab; } void operator()( const BlockedRange& range ) const { const float inf = 1e15f; int i, i1 = range.begin(), i2 = range.end(); int n = dst->cols; AutoBuffer _buf((n+2)*2*sizeof(float) + (n+2)*sizeof(int)); float* f = (float*)(uchar*)_buf; float* z = f + n; int* v = alignPtr((int*)(z + n + 1), sizeof(int)); for( i = i1; i < i2; i++ ) { float* d = dst->ptr(i); int p, q, k; v[0] = 0; z[0] = -inf; z[1] = inf; f[0] = d[0]; for( q = 1, k = 0; q < n; q++ ) { float fq = d[q]; f[q] = fq; for(;;k--) { p = v[k]; float s = (fq + sqr_tab[q] - d[p] - sqr_tab[p])*inv_tab[q - p]; if( s > z[k] ) { k++; v[k] = q; z[k] = s; z[k+1] = inf; break; } } } for( q = 0, k = 0; q < n; q++ ) { while( z[k+1] < q ) k++; p = v[k]; d[q] = std::sqrt(sqr_tab[std::abs(q - p)] + f[p]); } } } Mat* dst; const float* sqr_tab; const float* inv_tab; }; static void trueDistTrans( const Mat& src, Mat& dst ) { const float inf = 1e15f; CV_Assert( src.size() == dst.size() ); CV_Assert( src.type() == CV_8UC1 && dst.type() == CV_32FC1 ); int i, m = src.rows, n = src.cols; cv::AutoBuffer _buf(std::max(m*2*sizeof(float) + (m*3+1)*sizeof(int), n*2*sizeof(float))); // stage 1: compute 1d distance transform of each column float* sqr_tab = (float*)(uchar*)_buf; int* sat_tab = cv::alignPtr((int*)(sqr_tab + m*2), sizeof(int)); int shift = m*2; for( i = 0; i < m; i++ ) sqr_tab[i] = (float)(i*i); for( i = m; i < m*2; i++ ) sqr_tab[i] = inf; for( i = 0; i < shift; i++ ) sat_tab[i] = 0; for( ; i <= m*3; i++ ) sat_tab[i] = i - shift; cv::parallel_for(cv::BlockedRange(0, n), cv::DTColumnInvoker(&src, &dst, sat_tab, sqr_tab)); // stage 2: compute modified distance transform for each row float* inv_tab = sqr_tab + n; inv_tab[0] = sqr_tab[0] = 0.f; for( i = 1; i < n; i++ ) { inv_tab[i] = (float)(0.5/i); sqr_tab[i] = (float)(i*i); } cv::parallel_for(cv::BlockedRange(0, m), cv::DTRowInvoker(&dst, sqr_tab, inv_tab)); } /****************************************************************************************\ Non-inplace and Inplace 8u->8u Distance Transform for CityBlock (a.k.a. L1) metric (C) 2006 by Jay Stavinzky. \****************************************************************************************/ //BEGIN ATS ADDITION // 8-bit grayscale distance transform function static void distanceATS_L1_8u( const Mat& src, Mat& dst ) { int width = src.cols, height = src.rows; int a; uchar lut[256]; int x, y; const uchar *sbase = src.data; uchar *dbase = dst.data; int srcstep = (int)src.step; int dststep = (int)dst.step; CV_Assert( src.type() == CV_8UC1 && dst.type() == CV_8UC1 ); CV_Assert( src.size() == dst.size() ); ////////////////////// forward scan //////////////////////// for( x = 0; x < 256; x++ ) lut[x] = cv::saturate_cast(x+1); //init first pixel to max (we're going to be skipping it) dbase[0] = (uchar)(sbase[0] == 0 ? 0 : 255); //first row (scan west only, skip first pixel) for( x = 1; x < width; x++ ) dbase[x] = (uchar)(sbase[x] == 0 ? 0 : lut[dbase[x-1]]); for( y = 1; y < height; y++ ) { sbase += srcstep; dbase += dststep; //for left edge, scan north only a = sbase[0] == 0 ? 0 : lut[dbase[-dststep]]; dbase[0] = (uchar)a; for( x = 1; x < width; x++ ) { a = sbase[x] == 0 ? 0 : lut[MIN(a, dbase[x - dststep])]; dbase[x] = (uchar)a; } } ////////////////////// backward scan /////////////////////// a = dbase[width-1]; // do last row east pixel scan here (skip bottom right pixel) for( x = width - 2; x >= 0; x-- ) { a = lut[a]; dbase[x] = (uchar)(CV_CALC_MIN_8U(a, dbase[x])); } // right edge is the only error case for( y = height - 2; y >= 0; y-- ) { dbase -= dststep; // do right edge a = lut[dbase[width-1+dststep]]; dbase[width-1] = (uchar)(MIN(a, dbase[width-1])); for( x = width - 2; x >= 0; x-- ) { int b = dbase[x+dststep]; a = lut[MIN(a, b)]; dbase[x] = (uchar)(MIN(a, dbase[x])); } } } //END ATS ADDITION } // Wrapper function for distance transform group void cv::distanceTransform( InputArray _src, OutputArray _dst, OutputArray _labels, int distType, int maskSize, int labelType ) { Mat src = _src.getMat(), dst = _dst.getMat(), labels; bool need_labels = _labels.needed(); CV_Assert( src.type() == CV_8U ); if( dst.size == src.size && dst.type() == CV_8U && !need_labels && distType == CV_DIST_L1 ) { distanceATS_L1_8u(src, dst); return; } _dst.create( src.size(), CV_32F ); dst = _dst.getMat(); if( need_labels ) { CV_Assert( labelType == DIST_LABEL_PIXEL || labelType == DIST_LABEL_CCOMP ); _labels.create(src.size(), CV_32S); labels = _labels.getMat(); maskSize = CV_DIST_MASK_5; } CV_Assert( src.type() == CV_8UC1 ); float _mask[5] = {0}; if( maskSize != CV_DIST_MASK_3 && maskSize != CV_DIST_MASK_5 && maskSize != CV_DIST_MASK_PRECISE ) CV_Error( CV_StsBadSize, "Mask size should be 3 or 5 or 0 (presize)" ); if( distType == CV_DIST_C || distType == CV_DIST_L1 ) maskSize = !need_labels ? CV_DIST_MASK_3 : CV_DIST_MASK_5; else if( distType == CV_DIST_L2 && need_labels ) maskSize = CV_DIST_MASK_5; if( maskSize == CV_DIST_MASK_PRECISE ) { trueDistTrans( src, dst ); return; } CV_Assert( distType == CV_DIST_C || distType == CV_DIST_L1 || distType == CV_DIST_L2 ); getDistanceTransformMask( (distType == CV_DIST_C ? 0 : distType == CV_DIST_L1 ? 1 : 2) + maskSize*10, _mask ); Size size = src.size(); int border = maskSize == CV_DIST_MASK_3 ? 1 : 2; Mat temp( size.height + border*2, size.width + border*2, CV_32SC1 ); if( !need_labels ) { if( maskSize == CV_DIST_MASK_3 ) distanceTransform_3x3(src, temp, dst, _mask); else distanceTransform_5x5(src, temp, dst, _mask); } else { labels.setTo(Scalar::all(0)); if( labelType == CV_DIST_LABEL_CCOMP ) { Mat zpix = src == 0; connectedComponents(zpix, labels, 8, CV_32S); } else { int k = 1; for( int i = 0; i < src.rows; i++ ) { const uchar* srcptr = src.ptr(i); int* labelptr = labels.ptr(i); for( int j = 0; j < src.cols; j++ ) if( srcptr[j] == 0 ) labelptr[j] = k++; } } distanceTransformEx_5x5( src, temp, dst, labels, _mask ); } } void cv::distanceTransform( InputArray _src, OutputArray _dst, int distanceType, int maskSize ) { distanceTransform(_src, _dst, noArray(), distanceType, maskSize, DIST_LABEL_PIXEL); } CV_IMPL void cvDistTransform( const void* srcarr, void* dstarr, int distType, int maskSize, const float * /*mask*/, void* labelsarr, int labelType ) { cv::Mat src = cv::cvarrToMat(srcarr); const cv::Mat dst = cv::cvarrToMat(dstarr); const cv::Mat labels = cv::cvarrToMat(labelsarr); cv::distanceTransform(src, dst, labelsarr ? cv::_OutputArray(labels) : cv::_OutputArray(), distType, maskSize, labelType); } /* End of file. */