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opencv/modules/imgproc/src/thresh.cpp

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/*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"
#include "opencl_kernels.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();
size_t src_step = _src.step;
size_t dst_step = _dst.step;
if( _src.isContinuous() && _dst.isContinuous() )
{
roi.width *= roi.height;
roi.height = 1;
src_step = dst_step = roi.width;
}
#ifdef HAVE_TEGRA_OPTIMIZATION
if (tegra::thresh_8u(_src, _dst, roi.width, roi.height, thresh, maxval, type))
return;
#endif
#if defined(HAVE_IPP) && !defined(HAVE_IPP_ICV_ONLY)
IppiSize sz = { roi.width, roi.height };
switch( type )
{
case THRESH_TRUNC:
if (0 <= ippiThreshold_GT_8u_C1R(_src.data, (int)src_step, _dst.data, (int)dst_step, sz, thresh))
return;
break;
case THRESH_TOZERO:
if (0 <= ippiThreshold_LTVal_8u_C1R(_src.data, (int)src_step, _dst.data, (int)dst_step, sz, thresh+1, 0))
return;
break;
case THRESH_TOZERO_INV:
if (0 <= ippiThreshold_GTVal_8u_C1R(_src.data, (int)src_step, _dst.data, (int)dst_step, sz, thresh, 0))
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;
src_step = dst_step = roi.width;
}
#ifdef HAVE_TEGRA_OPTIMIZATION
if (tegra::thresh_16s(_src, _dst, roi.width, roi.height, thresh, maxval, type))
return;
#endif
#if defined(HAVE_IPP) && !defined(HAVE_IPP_ICV_ONLY)
IppiSize sz = { roi.width, roi.height };
switch( type )
{
case THRESH_TRUNC:
if (0 <= ippiThreshold_GT_16s_C1R(src, (int)src_step*sizeof(src[0]), dst, (int)dst_step*sizeof(dst[0]), sz, thresh))
return;
break;
case THRESH_TOZERO:
if (0 <= ippiThreshold_LTVal_16s_C1R(src, (int)src_step*sizeof(src[0]), dst, (int)dst_step*sizeof(dst[0]), sz, thresh+1, 0))
return;
break;
case THRESH_TOZERO_INV:
if (0 <= ippiThreshold_GTVal_16s_C1R(src, (int)src_step*sizeof(src[0]), dst, (int)dst_step*sizeof(dst[0]), sz, thresh, 0))
return;
break;
}
#endif
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;
}
#ifdef HAVE_TEGRA_OPTIMIZATION
if (tegra::thresh_32f(_src, _dst, roi.width, roi.height, thresh, maxval, type))
return;
#endif
#if defined(HAVE_IPP) && !defined(HAVE_IPP_ICV_ONLY)
IppiSize sz = { roi.width, roi.height };
switch( type )
{
case THRESH_TRUNC:
if (0 <= ippiThreshold_GT_32f_C1R(src, (int)src_step*sizeof(src[0]), dst, (int)dst_step*sizeof(dst[0]), sz, thresh))
return;
break;
case THRESH_TOZERO:
if (0 <= ippiThreshold_LTVal_32f_C1R(src, (int)src_step*sizeof(src[0]), dst, (int)dst_step*sizeof(dst[0]), sz, thresh+FLT_EPSILON, 0))
return;
break;
case THRESH_TOZERO_INV:
if (0 <= ippiThreshold_GTVal_32f_C1R(src, (int)src_step*sizeof(src[0]), dst, (int)dst_step*sizeof(dst[0]), sz, thresh, 0))
return;
break;
}
#endif
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 ParallelLoopBody
{
public:
ThresholdRunner(Mat _src, Mat _dst, double _thresh, double _maxval, int _thresholdType)
{
src = _src;
dst = _dst;
thresh = _thresh;
maxval = _maxval;
thresholdType = _thresholdType;
}
void operator () ( const Range& range ) const
{
int row0 = range.start;
int row1 = range.end;
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;
double thresh;
double maxval;
int thresholdType;
};
#ifdef HAVE_OPENCL
static bool ocl_threshold( InputArray _src, OutputArray _dst, double & thresh, double maxval, int thresh_type )
{
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type),
kercn = ocl::predictOptimalVectorWidth(_src, _dst), ktype = CV_MAKE_TYPE(depth, kercn);
bool doubleSupport = ocl::Device::getDefault().doubleFPConfig() > 0;
if ( !(thresh_type == THRESH_BINARY || thresh_type == THRESH_BINARY_INV || thresh_type == THRESH_TRUNC ||
thresh_type == THRESH_TOZERO || thresh_type == THRESH_TOZERO_INV) ||
(!doubleSupport && depth == CV_64F))
return false;
const char * const thresholdMap[] = { "THRESH_BINARY", "THRESH_BINARY_INV", "THRESH_TRUNC",
"THRESH_TOZERO", "THRESH_TOZERO_INV" };
ocl::Kernel k("threshold", ocl::imgproc::threshold_oclsrc,
format("-D %s -D T=%s -D T1=%s%s", thresholdMap[thresh_type],
ocl::typeToStr(ktype), ocl::typeToStr(depth),
doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
if (k.empty())
return false;
UMat src = _src.getUMat();
_dst.create(src.size(), type);
UMat dst = _dst.getUMat();
if (depth <= CV_32S)
thresh = cvFloor(thresh);
k.args(ocl::KernelArg::ReadOnlyNoSize(src), ocl::KernelArg::WriteOnly(dst, cn, kercn),
ocl::KernelArg::Constant(Mat(1, 1, depth, Scalar::all(thresh))),
ocl::KernelArg::Constant(Mat(1, 1, depth, Scalar::all(maxval))));
size_t globalsize[2] = { dst.cols * cn / kercn, dst.rows };
return k.run(2, globalsize, NULL, false);
}
#endif
}
double cv::threshold( InputArray _src, OutputArray _dst, double thresh, double maxval, int type )
{
CV_OCL_RUN_(_src.dims() <= 2 && _dst.isUMat(),
ocl_threshold(_src, _dst, thresh, maxval, type), thresh)
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();
if( src.depth() == CV_8U )
{
int ithresh = cvFloor(thresh);
thresh = ithresh;
int imaxval = cvRound(maxval);
if( type == THRESH_TRUNC )
imaxval = ithresh;
imaxval = saturate_cast<uchar>(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);
return thresh;
}
thresh = ithresh;
maxval = imaxval;
}
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<short>(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);
return thresh;
}
thresh = ithresh;
maxval = imaxval;
}
else if( src.depth() == CV_32F )
;
else
CV_Error( CV_StsUnsupportedFormat, "" );
parallel_for_(Range(0, dst.rows),
ThresholdRunner(src, dst, thresh, maxval, type),
dst.total()/(double)(1<<16));
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<uchar>(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. */
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