/*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) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., 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 void thresh_8u( const Mat& _src, Mat& _dst, uchar thresh, uchar maxval, int type ) { int i, j, j_scalar = 0; uchar tab[256]; Size roi = _src.size(); roi.width *= _src.channels(); if( _src.isContinuous() && _dst.isContinuous() ) { roi.width *= roi.height; roi.height = 1; } #ifdef HAVE_TEGRA_OPTIMIZATION switch( type ) { case THRESH_BINARY: if(tegra::thresh_8u_binary(_src, _dst, roi.width, roi.height, thresh, maxval)) return; break; case THRESH_BINARY_INV: if(tegra::thresh_8u_binary_inv(_src, _dst, roi.width, roi.height, thresh, maxval)) return; break; case THRESH_TRUNC: if(tegra::thresh_8u_trunc(_src, _dst, roi.width, roi.height, thresh)) return; break; case THRESH_TOZERO: if(tegra::thresh_8u_tozero(_src, _dst, roi.width, roi.height, thresh)) return; break; case THRESH_TOZERO_INV: if(tegra::thresh_8u_tozero_inv(_src, _dst, roi.width, roi.height, thresh)) return; break; } #endif switch( type ) { case THRESH_BINARY: for( i = 0; i <= thresh; i++ ) tab[i] = 0; for( ; i < 256; i++ ) tab[i] = maxval; break; case THRESH_BINARY_INV: for( i = 0; i <= thresh; i++ ) tab[i] = maxval; for( ; i < 256; i++ ) tab[i] = 0; break; case THRESH_TRUNC: for( i = 0; i <= thresh; i++ ) tab[i] = (uchar)i; for( ; i < 256; i++ ) tab[i] = thresh; break; case THRESH_TOZERO: for( i = 0; i <= thresh; i++ ) tab[i] = 0; for( ; i < 256; i++ ) tab[i] = (uchar)i; break; case THRESH_TOZERO_INV: for( i = 0; i <= thresh; i++ ) tab[i] = (uchar)i; for( ; i < 256; i++ ) tab[i] = 0; break; default: CV_Error( CV_StsBadArg, "Unknown threshold type" ); } #if CV_SSE2 if( checkHardwareSupport(CV_CPU_SSE2) ) { __m128i _x80 = _mm_set1_epi8('\x80'); __m128i thresh_u = _mm_set1_epi8(thresh); __m128i thresh_s = _mm_set1_epi8(thresh ^ 0x80); __m128i maxval_ = _mm_set1_epi8(maxval); j_scalar = roi.width & -8; for( i = 0; i < roi.height; i++ ) { const uchar* src = (const uchar*)(_src.data + _src.step*i); uchar* dst = (uchar*)(_dst.data + _dst.step*i); switch( type ) { case THRESH_BINARY: for( j = 0; j <= roi.width - 32; j += 32 ) { __m128i v0, v1; v0 = _mm_loadu_si128( (const __m128i*)(src + j) ); v1 = _mm_loadu_si128( (const __m128i*)(src + j + 16) ); v0 = _mm_cmpgt_epi8( _mm_xor_si128(v0, _x80), thresh_s ); v1 = _mm_cmpgt_epi8( _mm_xor_si128(v1, _x80), thresh_s ); v0 = _mm_and_si128( v0, maxval_ ); v1 = _mm_and_si128( v1, maxval_ ); _mm_storeu_si128( (__m128i*)(dst + j), v0 ); _mm_storeu_si128( (__m128i*)(dst + j + 16), v1 ); } for( ; j <= roi.width - 8; j += 8 ) { __m128i v0 = _mm_loadl_epi64( (const __m128i*)(src + j) ); v0 = _mm_cmpgt_epi8( _mm_xor_si128(v0, _x80), thresh_s ); v0 = _mm_and_si128( v0, maxval_ ); _mm_storel_epi64( (__m128i*)(dst + j), v0 ); } break; case THRESH_BINARY_INV: for( j = 0; j <= roi.width - 32; j += 32 ) { __m128i v0, v1; v0 = _mm_loadu_si128( (const __m128i*)(src + j) ); v1 = _mm_loadu_si128( (const __m128i*)(src + j + 16) ); v0 = _mm_cmpgt_epi8( _mm_xor_si128(v0, _x80), thresh_s ); v1 = _mm_cmpgt_epi8( _mm_xor_si128(v1, _x80), thresh_s ); v0 = _mm_andnot_si128( v0, maxval_ ); v1 = _mm_andnot_si128( v1, maxval_ ); _mm_storeu_si128( (__m128i*)(dst + j), v0 ); _mm_storeu_si128( (__m128i*)(dst + j + 16), v1 ); } for( ; j <= roi.width - 8; j += 8 ) { __m128i v0 = _mm_loadl_epi64( (const __m128i*)(src + j) ); v0 = _mm_cmpgt_epi8( _mm_xor_si128(v0, _x80), thresh_s ); v0 = _mm_andnot_si128( v0, maxval_ ); _mm_storel_epi64( (__m128i*)(dst + j), v0 ); } break; case THRESH_TRUNC: for( j = 0; j <= roi.width - 32; j += 32 ) { __m128i v0, v1; v0 = _mm_loadu_si128( (const __m128i*)(src + j) ); v1 = _mm_loadu_si128( (const __m128i*)(src + j + 16) ); v0 = _mm_subs_epu8( v0, _mm_subs_epu8( v0, thresh_u )); v1 = _mm_subs_epu8( v1, _mm_subs_epu8( v1, thresh_u )); _mm_storeu_si128( (__m128i*)(dst + j), v0 ); _mm_storeu_si128( (__m128i*)(dst + j + 16), v1 ); } for( ; j <= roi.width - 8; j += 8 ) { __m128i v0 = _mm_loadl_epi64( (const __m128i*)(src + j) ); v0 = _mm_subs_epu8( v0, _mm_subs_epu8( v0, thresh_u )); _mm_storel_epi64( (__m128i*)(dst + j), v0 ); } break; case THRESH_TOZERO: for( j = 0; j <= roi.width - 32; j += 32 ) { __m128i v0, v1; v0 = _mm_loadu_si128( (const __m128i*)(src + j) ); v1 = _mm_loadu_si128( (const __m128i*)(src + j + 16) ); v0 = _mm_and_si128( v0, _mm_cmpgt_epi8(_mm_xor_si128(v0, _x80), thresh_s )); v1 = _mm_and_si128( v1, _mm_cmpgt_epi8(_mm_xor_si128(v1, _x80), thresh_s )); _mm_storeu_si128( (__m128i*)(dst + j), v0 ); _mm_storeu_si128( (__m128i*)(dst + j + 16), v1 ); } for( ; j <= roi.width - 8; j += 8 ) { __m128i v0 = _mm_loadl_epi64( (const __m128i*)(src + j) ); v0 = _mm_and_si128( v0, _mm_cmpgt_epi8(_mm_xor_si128(v0, _x80), thresh_s )); _mm_storel_epi64( (__m128i*)(dst + j), v0 ); } break; case THRESH_TOZERO_INV: for( j = 0; j <= roi.width - 32; j += 32 ) { __m128i v0, v1; v0 = _mm_loadu_si128( (const __m128i*)(src + j) ); v1 = _mm_loadu_si128( (const __m128i*)(src + j + 16) ); v0 = _mm_andnot_si128( _mm_cmpgt_epi8(_mm_xor_si128(v0, _x80), thresh_s ), v0 ); v1 = _mm_andnot_si128( _mm_cmpgt_epi8(_mm_xor_si128(v1, _x80), thresh_s ), v1 ); _mm_storeu_si128( (__m128i*)(dst + j), v0 ); _mm_storeu_si128( (__m128i*)(dst + j + 16), v1 ); } for( ; j <= roi.width - 8; j += 8 ) { __m128i v0 = _mm_loadl_epi64( (const __m128i*)(src + j) ); v0 = _mm_andnot_si128( _mm_cmpgt_epi8(_mm_xor_si128(v0, _x80), thresh_s ), v0 ); _mm_storel_epi64( (__m128i*)(dst + j), v0 ); } break; } } } #endif if( j_scalar < roi.width ) { for( i = 0; i < roi.height; i++ ) { const uchar* src = (const uchar*)(_src.data + _src.step*i); uchar* dst = (uchar*)(_dst.data + _dst.step*i); j = j_scalar; #if CV_ENABLE_UNROLLED for( ; j <= roi.width - 4; j += 4 ) { uchar t0 = tab[src[j]]; uchar t1 = tab[src[j+1]]; dst[j] = t0; dst[j+1] = t1; t0 = tab[src[j+2]]; t1 = tab[src[j+3]]; dst[j+2] = t0; dst[j+3] = t1; } #endif for( ; j < roi.width; j++ ) dst[j] = tab[src[j]]; } } } static void thresh_16s( const Mat& _src, Mat& _dst, short thresh, short maxval, int type ) { int i, j; Size roi = _src.size(); roi.width *= _src.channels(); const short* src = (const short*)_src.data; short* dst = (short*)_dst.data; size_t src_step = _src.step/sizeof(src[0]); size_t dst_step = _dst.step/sizeof(dst[0]); #if CV_SSE2 volatile bool useSIMD = checkHardwareSupport(CV_CPU_SSE); #endif if( _src.isContinuous() && _dst.isContinuous() ) { roi.width *= roi.height; roi.height = 1; } switch( type ) { case THRESH_BINARY: for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step ) { j = 0; #if CV_SSE2 if( useSIMD ) { __m128i thresh8 = _mm_set1_epi16(thresh), maxval8 = _mm_set1_epi16(maxval); for( ; j <= roi.width - 16; j += 16 ) { __m128i v0, v1; v0 = _mm_loadu_si128( (const __m128i*)(src + j) ); v1 = _mm_loadu_si128( (const __m128i*)(src + j + 8) ); v0 = _mm_cmpgt_epi16( v0, thresh8 ); v1 = _mm_cmpgt_epi16( v1, thresh8 ); v0 = _mm_and_si128( v0, maxval8 ); v1 = _mm_and_si128( v1, maxval8 ); _mm_storeu_si128((__m128i*)(dst + j), v0 ); _mm_storeu_si128((__m128i*)(dst + j + 8), v1 ); } } #endif for( ; j < roi.width; j++ ) dst[j] = src[j] > thresh ? maxval : 0; } break; case THRESH_BINARY_INV: for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step ) { j = 0; #if CV_SSE2 if( useSIMD ) { __m128i thresh8 = _mm_set1_epi16(thresh), maxval8 = _mm_set1_epi16(maxval); for( ; j <= roi.width - 16; j += 16 ) { __m128i v0, v1; v0 = _mm_loadu_si128( (const __m128i*)(src + j) ); v1 = _mm_loadu_si128( (const __m128i*)(src + j + 8) ); v0 = _mm_cmpgt_epi16( v0, thresh8 ); v1 = _mm_cmpgt_epi16( v1, thresh8 ); v0 = _mm_andnot_si128( v0, maxval8 ); v1 = _mm_andnot_si128( v1, maxval8 ); _mm_storeu_si128((__m128i*)(dst + j), v0 ); _mm_storeu_si128((__m128i*)(dst + j + 8), v1 ); } } #endif for( ; j < roi.width; j++ ) dst[j] = src[j] <= thresh ? maxval : 0; } break; case THRESH_TRUNC: for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step ) { j = 0; #if CV_SSE2 if( useSIMD ) { __m128i thresh8 = _mm_set1_epi16(thresh); for( ; j <= roi.width - 16; j += 16 ) { __m128i v0, v1; v0 = _mm_loadu_si128( (const __m128i*)(src + j) ); v1 = _mm_loadu_si128( (const __m128i*)(src + j + 8) ); v0 = _mm_min_epi16( v0, thresh8 ); v1 = _mm_min_epi16( v1, thresh8 ); _mm_storeu_si128((__m128i*)(dst + j), v0 ); _mm_storeu_si128((__m128i*)(dst + j + 8), v1 ); } } #endif for( ; j < roi.width; j++ ) dst[j] = std::min(src[j], thresh); } break; case THRESH_TOZERO: for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step ) { j = 0; #if CV_SSE2 if( useSIMD ) { __m128i thresh8 = _mm_set1_epi16(thresh); for( ; j <= roi.width - 16; j += 16 ) { __m128i v0, v1; v0 = _mm_loadu_si128( (const __m128i*)(src + j) ); v1 = _mm_loadu_si128( (const __m128i*)(src + j + 8) ); v0 = _mm_and_si128(v0, _mm_cmpgt_epi16(v0, thresh8)); v1 = _mm_and_si128(v1, _mm_cmpgt_epi16(v1, thresh8)); _mm_storeu_si128((__m128i*)(dst + j), v0 ); _mm_storeu_si128((__m128i*)(dst + j + 8), v1 ); } } #endif for( ; j < roi.width; j++ ) { short v = src[j]; dst[j] = v > thresh ? v : 0; } } break; case THRESH_TOZERO_INV: for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step ) { j = 0; #if CV_SSE2 if( useSIMD ) { __m128i thresh8 = _mm_set1_epi16(thresh); for( ; j <= roi.width - 16; j += 16 ) { __m128i v0, v1; v0 = _mm_loadu_si128( (const __m128i*)(src + j) ); v1 = _mm_loadu_si128( (const __m128i*)(src + j + 8) ); v0 = _mm_andnot_si128(_mm_cmpgt_epi16(v0, thresh8), v0); v1 = _mm_andnot_si128(_mm_cmpgt_epi16(v1, thresh8), v1); _mm_storeu_si128((__m128i*)(dst + j), v0 ); _mm_storeu_si128((__m128i*)(dst + j + 8), v1 ); } } #endif for( ; j < roi.width; j++ ) { short v = src[j]; dst[j] = v <= thresh ? v : 0; } } break; default: return CV_Error( CV_StsBadArg, "" ); } } static void thresh_32f( const Mat& _src, Mat& _dst, float thresh, float maxval, int type ) { int i, j; Size roi = _src.size(); roi.width *= _src.channels(); const float* src = (const float*)_src.data; float* dst = (float*)_dst.data; size_t src_step = _src.step/sizeof(src[0]); size_t dst_step = _dst.step/sizeof(dst[0]); #if CV_SSE2 volatile bool useSIMD = checkHardwareSupport(CV_CPU_SSE); #endif if( _src.isContinuous() && _dst.isContinuous() ) { roi.width *= roi.height; roi.height = 1; } switch( type ) { case THRESH_BINARY: for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step ) { j = 0; #if CV_SSE2 if( useSIMD ) { __m128 thresh4 = _mm_set1_ps(thresh), maxval4 = _mm_set1_ps(maxval); for( ; j <= roi.width - 8; j += 8 ) { __m128 v0, v1; v0 = _mm_loadu_ps( src + j ); v1 = _mm_loadu_ps( src + j + 4 ); v0 = _mm_cmpgt_ps( v0, thresh4 ); v1 = _mm_cmpgt_ps( v1, thresh4 ); v0 = _mm_and_ps( v0, maxval4 ); v1 = _mm_and_ps( v1, maxval4 ); _mm_storeu_ps( dst + j, v0 ); _mm_storeu_ps( dst + j + 4, v1 ); } } #endif for( ; j < roi.width; j++ ) dst[j] = src[j] > thresh ? maxval : 0; } break; case THRESH_BINARY_INV: for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step ) { j = 0; #if CV_SSE2 if( useSIMD ) { __m128 thresh4 = _mm_set1_ps(thresh), maxval4 = _mm_set1_ps(maxval); for( ; j <= roi.width - 8; j += 8 ) { __m128 v0, v1; v0 = _mm_loadu_ps( src + j ); v1 = _mm_loadu_ps( src + j + 4 ); v0 = _mm_cmple_ps( v0, thresh4 ); v1 = _mm_cmple_ps( v1, thresh4 ); v0 = _mm_and_ps( v0, maxval4 ); v1 = _mm_and_ps( v1, maxval4 ); _mm_storeu_ps( dst + j, v0 ); _mm_storeu_ps( dst + j + 4, v1 ); } } #endif for( ; j < roi.width; j++ ) dst[j] = src[j] <= thresh ? maxval : 0; } break; case THRESH_TRUNC: for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step ) { j = 0; #if CV_SSE2 if( useSIMD ) { __m128 thresh4 = _mm_set1_ps(thresh); for( ; j <= roi.width - 8; j += 8 ) { __m128 v0, v1; v0 = _mm_loadu_ps( src + j ); v1 = _mm_loadu_ps( src + j + 4 ); v0 = _mm_min_ps( v0, thresh4 ); v1 = _mm_min_ps( v1, thresh4 ); _mm_storeu_ps( dst + j, v0 ); _mm_storeu_ps( dst + j + 4, v1 ); } } #endif for( ; j < roi.width; j++ ) dst[j] = std::min(src[j], thresh); } break; case THRESH_TOZERO: for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step ) { j = 0; #if CV_SSE2 if( useSIMD ) { __m128 thresh4 = _mm_set1_ps(thresh); for( ; j <= roi.width - 8; j += 8 ) { __m128 v0, v1; v0 = _mm_loadu_ps( src + j ); v1 = _mm_loadu_ps( src + j + 4 ); v0 = _mm_and_ps(v0, _mm_cmpgt_ps(v0, thresh4)); v1 = _mm_and_ps(v1, _mm_cmpgt_ps(v1, thresh4)); _mm_storeu_ps( dst + j, v0 ); _mm_storeu_ps( dst + j + 4, v1 ); } } #endif for( ; j < roi.width; j++ ) { float v = src[j]; dst[j] = v > thresh ? v : 0; } } break; case THRESH_TOZERO_INV: for( i = 0; i < roi.height; i++, src += src_step, dst += dst_step ) { j = 0; #if CV_SSE2 if( useSIMD ) { __m128 thresh4 = _mm_set1_ps(thresh); for( ; j <= roi.width - 8; j += 8 ) { __m128 v0, v1; v0 = _mm_loadu_ps( src + j ); v1 = _mm_loadu_ps( src + j + 4 ); v0 = _mm_and_ps(v0, _mm_cmple_ps(v0, thresh4)); v1 = _mm_and_ps(v1, _mm_cmple_ps(v1, thresh4)); _mm_storeu_ps( dst + j, v0 ); _mm_storeu_ps( dst + j + 4, v1 ); } } #endif for( ; j < roi.width; j++ ) { float v = src[j]; dst[j] = v <= thresh ? v : 0; } } break; default: return CV_Error( CV_StsBadArg, "" ); } } static double getThreshVal_Otsu_8u( const Mat& _src ) { Size size = _src.size(); if( _src.isContinuous() ) { size.width *= size.height; size.height = 1; } const int N = 256; int i, j, h[N] = {0}; for( i = 0; i < size.height; i++ ) { const uchar* src = _src.data + _src.step*i; j = 0; #if CV_ENABLE_UNROLLED for( ; j <= size.width - 4; j += 4 ) { int v0 = src[j], v1 = src[j+1]; h[v0]++; h[v1]++; v0 = src[j+2]; v1 = src[j+3]; h[v0]++; h[v1]++; } #endif for( ; j < size.width; j++ ) h[src[j]]++; } double mu = 0, scale = 1./(size.width*size.height); for( i = 0; i < N; i++ ) mu += i*(double)h[i]; mu *= scale; double mu1 = 0, q1 = 0; double max_sigma = 0, max_val = 0; for( i = 0; i < N; i++ ) { double p_i, q2, mu2, sigma; p_i = h[i]*scale; mu1 *= q1; q1 += p_i; q2 = 1. - q1; if( std::min(q1,q2) < FLT_EPSILON || std::max(q1,q2) > 1. - FLT_EPSILON ) continue; mu1 = (mu1 + i*p_i)/q1; mu2 = (mu - q1*mu1)/q2; sigma = q1*q2*(mu1 - mu2)*(mu1 - mu2); if( sigma > max_sigma ) { max_sigma = sigma; max_val = i; } } return max_val; } class ThresholdRunner { public: ThresholdRunner(Mat _src, Mat _dst, int _nStripes, double _thresh, double _maxval, int _thresholdType) { src = _src; dst = _dst; nStripes = _nStripes; thresh = _thresh; maxval = _maxval; thresholdType = _thresholdType; } void operator () ( const BlockedRange& range ) const { int row0 = std::min(cvRound(range.begin() * src.rows / nStripes), src.rows); int row1 = std::min(cvRound(range.end() * src.rows / nStripes), src.rows); if(0) printf("Size = (%d, %d), range[%d,%d), row0 = %d, row1 = %d\n", src.rows, src.cols, range.begin(), range.end(), row0, row1); Mat srcStripe = src.rowRange(row0, row1); Mat dstStripe = dst.rowRange(row0, row1); if (srcStripe.depth() == CV_8U) { thresh_8u( srcStripe, dstStripe, (uchar)thresh, (uchar)maxval, thresholdType ); } else if( srcStripe.depth() == CV_16S ) { thresh_16s( srcStripe, dstStripe, (short)thresh, (short)maxval, thresholdType ); } else if( srcStripe.depth() == CV_32F ) { thresh_32f( srcStripe, dstStripe, (float)thresh, (float)maxval, thresholdType ); } } private: Mat src; Mat dst; int nStripes; double thresh; double maxval; int thresholdType; }; } double cv::threshold( InputArray _src, OutputArray _dst, double thresh, double maxval, int type ) { Mat src = _src.getMat(); bool use_otsu = (type & THRESH_OTSU) != 0; type &= THRESH_MASK; if( use_otsu ) { CV_Assert( src.type() == CV_8UC1 ); thresh = getThreshVal_Otsu_8u(src); } _dst.create( src.size(), src.type() ); Mat dst = _dst.getMat(); int nStripes = 1; #if defined HAVE_TBB && defined HAVE_TEGRA_OPTIMIZATION nStripes = 4; #endif if( src.depth() == CV_8U ) { int ithresh = cvFloor(thresh); thresh = ithresh; int imaxval = cvRound(maxval); if( type == THRESH_TRUNC ) imaxval = ithresh; imaxval = saturate_cast(imaxval); if( ithresh < 0 || ithresh >= 255 ) { if( type == THRESH_BINARY || type == THRESH_BINARY_INV || ((type == THRESH_TRUNC || type == THRESH_TOZERO_INV) && ithresh < 0) || (type == THRESH_TOZERO && ithresh >= 255) ) { int v = type == THRESH_BINARY ? (ithresh >= 255 ? 0 : imaxval) : type == THRESH_BINARY_INV ? (ithresh >= 255 ? imaxval : 0) : /*type == THRESH_TRUNC ? imaxval :*/ 0; dst.setTo(v); } else src.copyTo(dst); } else { //thresh_8u( src, dst, (uchar)ithresh, (uchar)imaxval, type ); parallel_for(BlockedRange(0, nStripes), ThresholdRunner(src, dst, nStripes, (uchar)ithresh, (uchar)imaxval, type)); } } else if( src.depth() == CV_16S ) { int ithresh = cvFloor(thresh); thresh = ithresh; int imaxval = cvRound(maxval); if( type == THRESH_TRUNC ) imaxval = ithresh; imaxval = saturate_cast(imaxval); if( ithresh < SHRT_MIN || ithresh >= SHRT_MAX ) { if( type == THRESH_BINARY || type == THRESH_BINARY_INV || ((type == THRESH_TRUNC || type == THRESH_TOZERO_INV) && ithresh < SHRT_MIN) || (type == THRESH_TOZERO && ithresh >= SHRT_MAX) ) { int v = type == THRESH_BINARY ? (ithresh >= SHRT_MAX ? 0 : imaxval) : type == THRESH_BINARY_INV ? (ithresh >= SHRT_MAX ? imaxval : 0) : /*type == THRESH_TRUNC ? imaxval :*/ 0; dst.setTo(v); } else src.copyTo(dst); } else { //thresh_16s( src, dst, (short)ithresh, (short)imaxval, type ); parallel_for(BlockedRange(0, nStripes), ThresholdRunner(src, dst, nStripes, (short)ithresh, (short)imaxval, type)); } } else if( src.depth() == CV_32F ) { //thresh_32f( src, dst, (float)thresh, (float)maxval, type ); parallel_for(BlockedRange(0, nStripes), ThresholdRunner(src, dst, nStripes, (float)thresh, (float)maxval, type)); } else CV_Error( CV_StsUnsupportedFormat, "" ); return thresh; } void cv::adaptiveThreshold( InputArray _src, OutputArray _dst, double maxValue, int method, int type, int blockSize, double delta ) { Mat src = _src.getMat(); CV_Assert( src.type() == CV_8UC1 ); CV_Assert( blockSize % 2 == 1 && blockSize > 1 ); Size size = src.size(); _dst.create( size, src.type() ); Mat dst = _dst.getMat(); if( maxValue < 0 ) { dst = Scalar(0); return; } Mat mean; if( src.data != dst.data ) mean = dst; if( method == ADAPTIVE_THRESH_MEAN_C ) boxFilter( src, mean, src.type(), Size(blockSize, blockSize), Point(-1,-1), true, BORDER_REPLICATE ); else if( method == ADAPTIVE_THRESH_GAUSSIAN_C ) GaussianBlur( src, mean, Size(blockSize, blockSize), 0, 0, BORDER_REPLICATE ); else CV_Error( CV_StsBadFlag, "Unknown/unsupported adaptive threshold method" ); int i, j; uchar imaxval = saturate_cast(maxValue); int idelta = type == THRESH_BINARY ? cvCeil(delta) : cvFloor(delta); uchar tab[768]; if( type == CV_THRESH_BINARY ) for( i = 0; i < 768; i++ ) tab[i] = (uchar)(i - 255 > -idelta ? imaxval : 0); else if( type == CV_THRESH_BINARY_INV ) for( i = 0; i < 768; i++ ) tab[i] = (uchar)(i - 255 <= -idelta ? imaxval : 0); else CV_Error( CV_StsBadFlag, "Unknown/unsupported threshold type" ); if( src.isContinuous() && mean.isContinuous() && dst.isContinuous() ) { size.width *= size.height; size.height = 1; } for( i = 0; i < size.height; i++ ) { const uchar* sdata = src.data + src.step*i; const uchar* mdata = mean.data + mean.step*i; uchar* ddata = dst.data + dst.step*i; for( j = 0; j < size.width; j++ ) ddata[j] = tab[sdata[j] - mdata[j] + 255]; } } CV_IMPL double cvThreshold( const void* srcarr, void* dstarr, double thresh, double maxval, int type ) { cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr), dst0 = dst; CV_Assert( src.size == dst.size && src.channels() == dst.channels() && (src.depth() == dst.depth() || dst.depth() == CV_8U)); thresh = cv::threshold( src, dst, thresh, maxval, type ); if( dst0.data != dst.data ) dst.convertTo( dst0, dst0.depth() ); return thresh; } CV_IMPL void cvAdaptiveThreshold( const void *srcIm, void *dstIm, double maxValue, int method, int type, int blockSize, double delta ) { cv::Mat src = cv::cvarrToMat(srcIm), dst = cv::cvarrToMat(dstIm); CV_Assert( src.size == dst.size && src.type() == dst.type() ); cv::adaptiveThreshold( src, dst, maxValue, method, type, blockSize, delta ); } /* End of file. */