/*M///////////////////////////////////////////////////////////////////////////////////////
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// Intel License Agreement
// For Open Source Computer Vision Library
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// are permitted provided that the following conditions are met:
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// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
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// * Redistribution's in binary form must reproduce the above copyright notice,
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//M*/
#include "_cv.h"
#if 0
IPCVAPI(CvStatus, icvCalcContrastHist8uC1R, ( uchar** img, int step, CvSize size,
CvHistogram* hist, int dont_clear ))
IPCVAPI(CvStatus, icvCalcContrastHistMask8uC1R, ( uchar** img, int step,
uchar* mask, int mask_step, CvSize size,
CvHistogram* hist, int dont_clear ))
/*F///////////////////////////////////////////////////////////////////////////////////////
// Name: icvCalcContrastHist8uC1R
// Purpose: Calculating the histogram of contrast from one-channel images
// Context:
// Parameters:
// Returns:
// Notes: if dont_clear parameter is NULL then histogram clearing before
// calculating (all values sets to NULL)
//F*/
static CvStatus CV_STDCALL
icvCalcContrastHist8uC1R( uchar** img, int step, CvSize size,
CvHistogram* hist, int dont_clear )
{
int i, j, t, x = 0, y = 0;
int dims;
if( !hist || !img )
return CV_NULLPTR_ERR;
dims = hist->c_dims;
if( dims != 1 )
return CV_BADSIZE_ERR;
if( hist->type != CV_HIST_ARRAY )
return CV_BADFLAG_ERR;
for( i = 0; i < dims; i++ )
if( !img[i] )
return CV_NULLPTR_ERR;
for( i = 0; i < hist->c_dims; i++ )
{
if( !hist->thresh[i] )
return CV_NULLPTR_ERR;
assert( hist->chdims[i] );
}
j = hist->dims[0] * hist->mdims[0];
int *n = (int *)cvAlloc( (size_t)hist->dims[0] * sizeof( int ));
if( hist->type == CV_HIST_ARRAY )
{
if( !dont_clear )
for( i = 0; i < j; i++ )
{
hist->array[i] = 0;
n[i] = 0;
}
switch (hist->c_dims)
{
case 1:
{
uchar *data0 = img[0];
int *array = (int *) hist->array;
int *chdims = hist->chdims[0];
for( i = 0; i < j; i++ )
array[i] = cvRound( hist->array[i] );
for( y = 0; y < size.height; y++, data0 += step )
{
for( x = 0; x <= size.width - 1; x += 2 )
{
int v1_r = MIN( data0[x], data0[x + 1] );
int v2_r = MAX( data0[x], data0[x + 1] );
// calculate contrast for the right-left pair
for( t = v1_r; t < v2_r; t++ )
{
int val0 = chdims[t + 128];
array[val0] += MIN( t - v1_r, v2_r - t );
n[val0]++;
}
if( y < size.height - 1 )
{
int v1_d = MIN( data0[x], data0[x + step] );
int v2_d = MAX( data0[x], data0[x + step] );
// calculate contrast for the top-down pair
for( t = v1_d; t < v2_d; t++ )
{
int val0 = chdims[t + 128];
array[val0] += MIN( t - v1_d, v2_d - t );
n[val0]++;
}
}
}
}
// convert int to float
for( i = 0; i < j; i++ )
{
if( n[i] != 0 )
hist->array[i] = (float) array[i] / n[i];
else
hist->array[i] = 0;
}
}
break;
default:
return CV_BADSIZE_ERR;
}
}
cvFree( &n );
return CV_NO_ERR;
}
/*F///////////////////////////////////////////////////////////////////////////////////////
// Name: icvCalcContrastHistMask8uC1R
// Purpose: Calculating the mask histogram of contrast from one-channel images
// Context:
// Parameters:
// Returns:
// Notes: if dont_clear parameter is NULL then histogram clearing before
// calculating (all values sets to NULL)
//F*/
static CvStatus CV_STDCALL
icvCalcContrastHistMask8uC1R( uchar** img, int step, uchar* mask, int mask_step,
CvSize size, CvHistogram * hist, int dont_clear )
{
int i, j, t, x = 0, y = 0;
int dims;
if( !hist || !img || !mask )
return CV_NULLPTR_ERR;
dims = hist->c_dims;
if( dims != 1 )
return CV_BADSIZE_ERR;
if( hist->type != CV_HIST_ARRAY )
return CV_BADFLAG_ERR;
for( i = 0; i < dims; i++ )
if( !img[i] )
return CV_NULLPTR_ERR;
for( i = 0; i < hist->c_dims; i++ )
{
if( !hist->thresh[i] )
return CV_NULLPTR_ERR;
assert( hist->chdims[i] );
}
j = hist->dims[0] * hist->mdims[0];
int *n = (int *)cvAlloc( (size_t) hist->dims[0] * sizeof( int ));
if( hist->type == CV_HIST_ARRAY )
{
if( !dont_clear )
for( i = 0; i < j; i++ )
{
hist->array[i] = 0;
n[i] = 0;
}
switch (hist->c_dims)
{
case 1:
{
uchar *data0 = img[0];
uchar *maskp = mask;
int *array = (int *) hist->array;
int *chdims = hist->chdims[0];
for( i = 0; i < j; i++ )
array[i] = cvRound( hist->array[i] );
for( y = 0; y < size.height; y++, data0 += step, maskp += mask_step )
{
for( x = 0; x <= size.width - 2; x++ )
{
if( maskp[x] )
{
if( maskp[x + 1] )
{
int v1_r = MIN( data0[x], data0[x + 1] );
int v2_r = MAX( data0[x], data0[x + 1] );
// calculate contrast for the right-left pair
for( t = v1_r; t < v2_r; t++ )
{
int val0 = chdims[t + 128];
array[val0] += MIN( t - v1_r, v2_r - t );
n[val0]++;
}
}
if( y < size.height - 1 )
{
if( maskp[x + mask_step] )
{
int v1_d = MIN( data0[x], data0[x + step] );
int v2_d = MAX( data0[x], data0[x + step] );
// calculate contrast for the top-down pair
for( t = v1_d; t < v2_d; t++ )
{
int val0 = chdims[t + 128];
array[val0] += MIN( t - v1_d, v2_d - t );
n[val0]++;
}
}
}
}
}
}
// convert int to float
for( i = 0; i < j; i++ )
{
if( n[i] != 0 )
hist->array[i] = (float) array[i] / n[i];
else
hist->array[i] = 0;
}
}
break;
default:
return CV_BADSIZE_ERR;
}
}
cvFree( &n );
return CV_NO_ERR;
}
/*
CV_IMPL void cvCalcContrastHist( IplImage** img, CvHistogram* hist, int dont_clear )
{
CV_FUNCNAME( "cvCalcContrastHist" );
uchar* data[CV_HIST_MAX_DIM];
int step = 0;
CvSize roi = {0,0};
__BEGIN__;
{for( int i = 0; i < hist->c_dims; i++ )
CV_CALL( CV_CHECK_IMAGE( img[i] ) );}
{for( int i = 0; i < hist->c_dims; i++ )
cvGetImageRawData( img[i], &data[i], &step, &roi );}
if(img[0]->nChannels != 1)
CV_ERROR( IPL_BadNumChannels, "bad channels numbers" );
if(img[0]->depth != IPL_DEPTH_8U)
CV_ERROR( IPL_BadDepth, "bad image depth" );
switch(img[0]->depth)
{
case IPL_DEPTH_8U:
IPPI_CALL( icvCalcContrastHist8uC1R( data, step, roi, hist, dont_clear ) );
break;
default: CV_ERROR( IPL_BadDepth, "bad image depth" );
}
__CLEANUP__;
__END__;
}
*/
CV_IMPL void
cvCalcContrastHist( IplImage ** img, CvHistogram * hist, int dont_clear, IplImage * mask )
{
CV_FUNCNAME( "cvCalcContrastHist" );
uchar *data[CV_HIST_MAX_DIM];
uchar *mask_data = 0;
int step = 0;
int mask_step = 0;
CvSize roi = { 0, 0 };
__BEGIN__;
{
for( int i = 0; i < hist->c_dims; i++ )
CV_CALL( CV_CHECK_IMAGE( img[i] ));
}
if( mask )
{
CV_CALL( CV_CHECK_IMAGE( mask ));
if( mask->depth != IPL_DEPTH_8U )
CV_ERROR( CV_BadDepth, "bad mask depth" );
cvGetImageRawData( mask, &mask_data, &mask_step, 0 );
}
{
for( int i = 0; i < hist->c_dims; i++ )
cvGetImageRawData( img[i], &data[i], &step, &roi );
}
if( img[0]->nChannels != 1 )
CV_ERROR( CV_BadNumChannels, "bad channels numbers" );
if( img[0]->depth != IPL_DEPTH_8U )
CV_ERROR( CV_BadDepth, "bad image depth" );
switch (img[0]->depth)
{
case IPL_DEPTH_8U:
if( !mask )
{
IPPI_CALL( icvCalcContrastHist8uC1R( data, step, roi, hist, dont_clear ));
}
else
{
IPPI_CALL( icvCalcContrastHistMask8uC1R( data, step, mask_data,
mask_step, roi, hist, dont_clear ));
}
break;
default:
CV_ERROR( CV_BadDepth, "bad image depth" );
}
__CLEANUP__;
__END__;
}
#endif