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| //M*/ |
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| /****************************************************************************************\ |
| |
| Calculation of a texture descriptors from GLCM (Grey Level Co-occurrence Matrix'es) |
| The code was submitted by Daniel Eaton [danieljameseaton@yahoo.com] |
| |
| \****************************************************************************************/ |
| |
| #include "_cvaux.h" |
| |
| #include <math.h> |
| #include <assert.h> |
| |
| #define CV_MAX_NUM_GREY_LEVELS_8U 256 |
| |
| struct CvGLCM |
| { |
| int matrixSideLength; |
| int numMatrices; |
| double*** matrices; |
| |
| int numLookupTableElements; |
| int forwardLookupTable[CV_MAX_NUM_GREY_LEVELS_8U]; |
| int reverseLookupTable[CV_MAX_NUM_GREY_LEVELS_8U]; |
| |
| double** descriptors; |
| int numDescriptors; |
| int descriptorOptimizationType; |
| int optimizationType; |
| }; |
| |
| |
| static void icvCreateGLCM_LookupTable_8u_C1R( const uchar* srcImageData, int srcImageStep, |
| CvSize srcImageSize, CvGLCM* destGLCM, |
| int* steps, int numSteps, int* memorySteps ); |
| |
| static void |
| icvCreateGLCMDescriptors_AllowDoubleNest( CvGLCM* destGLCM, int matrixIndex ); |
| |
| |
| CV_IMPL CvGLCM* |
| cvCreateGLCM( const IplImage* srcImage, |
| int stepMagnitude, |
| const int* srcStepDirections,/* should be static array.. |
| or if not the user should handle de-allocation */ |
| int numStepDirections, |
| int optimizationType ) |
| { |
| static const int defaultStepDirections[] = { 0,1, -1,1, -1,0, -1,-1 }; |
| |
| int* memorySteps = 0; |
| CvGLCM* newGLCM = 0; |
| int* stepDirections = 0; |
| |
| CV_FUNCNAME( "cvCreateGLCM" ); |
| |
| __BEGIN__; |
| |
| uchar* srcImageData = 0; |
| CvSize srcImageSize; |
| int srcImageStep; |
| int stepLoop; |
| const int maxNumGreyLevels8u = CV_MAX_NUM_GREY_LEVELS_8U; |
| |
| if( !srcImage ) |
| CV_ERROR( CV_StsNullPtr, "" ); |
| |
| if( srcImage->nChannels != 1 ) |
| CV_ERROR( CV_BadNumChannels, "Number of channels must be 1"); |
| |
| if( srcImage->depth != IPL_DEPTH_8U ) |
| CV_ERROR( CV_BadDepth, "Depth must be equal IPL_DEPTH_8U"); |
| |
| // no Directions provided, use the default ones - 0 deg, 45, 90, 135 |
| if( !srcStepDirections ) |
| { |
| srcStepDirections = defaultStepDirections; |
| } |
| |
| CV_CALL( stepDirections = (int*)cvAlloc( numStepDirections*2*sizeof(stepDirections[0]))); |
| memcpy( stepDirections, srcStepDirections, numStepDirections*2*sizeof(stepDirections[0])); |
| |
| cvGetImageRawData( srcImage, &srcImageData, &srcImageStep, &srcImageSize ); |
| |
| // roll together Directions and magnitudes together with knowledge of image (step) |
| CV_CALL( memorySteps = (int*)cvAlloc( numStepDirections*sizeof(memorySteps[0]))); |
| |
| for( stepLoop = 0; stepLoop < numStepDirections; stepLoop++ ) |
| { |
| stepDirections[stepLoop*2 + 0] *= stepMagnitude; |
| stepDirections[stepLoop*2 + 1] *= stepMagnitude; |
| |
| memorySteps[stepLoop] = stepDirections[stepLoop*2 + 0]*srcImageStep + |
| stepDirections[stepLoop*2 + 1]; |
| } |
| |
| CV_CALL( newGLCM = (CvGLCM*)cvAlloc(sizeof(newGLCM))); |
| memset( newGLCM, 0, sizeof(newGLCM) ); |
| |
| newGLCM->matrices = 0; |
| newGLCM->numMatrices = numStepDirections; |
| newGLCM->optimizationType = optimizationType; |
| |
| if( optimizationType <= CV_GLCM_OPTIMIZATION_LUT ) |
| { |
| int lookupTableLoop, imageColLoop, imageRowLoop, lineOffset = 0; |
| |
| // if optimization type is set to lut, then make one for the image |
| if( optimizationType == CV_GLCM_OPTIMIZATION_LUT ) |
| { |
| for( imageRowLoop = 0; imageRowLoop < srcImageSize.height; |
| imageRowLoop++, lineOffset += srcImageStep ) |
| { |
| for( imageColLoop = 0; imageColLoop < srcImageSize.width; imageColLoop++ ) |
| { |
| newGLCM->forwardLookupTable[srcImageData[lineOffset+imageColLoop]]=1; |
| } |
| } |
| |
| newGLCM->numLookupTableElements = 0; |
| |
| for( lookupTableLoop = 0; lookupTableLoop < maxNumGreyLevels8u; lookupTableLoop++ ) |
| { |
| if( newGLCM->forwardLookupTable[ lookupTableLoop ] != 0 ) |
| { |
| newGLCM->forwardLookupTable[ lookupTableLoop ] = |
| newGLCM->numLookupTableElements; |
| newGLCM->reverseLookupTable[ newGLCM->numLookupTableElements ] = |
| lookupTableLoop; |
| |
| newGLCM->numLookupTableElements++; |
| } |
| } |
| } |
| // otherwise make a "LUT" which contains all the gray-levels (for code-reuse) |
| else if( optimizationType == CV_GLCM_OPTIMIZATION_NONE ) |
| { |
| for( lookupTableLoop = 0; lookupTableLoop <maxNumGreyLevels8u; lookupTableLoop++ ) |
| { |
| newGLCM->forwardLookupTable[ lookupTableLoop ] = lookupTableLoop; |
| newGLCM->reverseLookupTable[ lookupTableLoop ] = lookupTableLoop; |
| } |
| newGLCM->numLookupTableElements = maxNumGreyLevels8u; |
| } |
| |
| newGLCM->matrixSideLength = newGLCM->numLookupTableElements; |
| icvCreateGLCM_LookupTable_8u_C1R( srcImageData, srcImageStep, srcImageSize, |
| newGLCM, stepDirections, |
| numStepDirections, memorySteps ); |
| } |
| else if( optimizationType == CV_GLCM_OPTIMIZATION_HISTOGRAM ) |
| { |
| CV_ERROR( CV_StsBadFlag, "Histogram-based method is not implemented" ); |
| |
| /* newGLCM->numMatrices *= 2; |
| newGLCM->matrixSideLength = maxNumGreyLevels8u*2; |
| |
| icvCreateGLCM_Histogram_8uC1R( srcImageStep, srcImageSize, srcImageData, |
| newGLCM, numStepDirections, |
| stepDirections, memorySteps ); |
| */ |
| } |
| |
| __END__; |
| |
| cvFree( &memorySteps ); |
| cvFree( &stepDirections ); |
| |
| if( cvGetErrStatus() < 0 ) |
| { |
| cvFree( &newGLCM ); |
| } |
| |
| return newGLCM; |
| } |
| |
| |
| CV_IMPL void |
| cvReleaseGLCM( CvGLCM** GLCM, int flag ) |
| { |
| CV_FUNCNAME( "cvReleaseGLCM" ); |
| |
| __BEGIN__; |
| |
| int matrixLoop; |
| |
| if( !GLCM ) |
| CV_ERROR( CV_StsNullPtr, "" ); |
| |
| if( *GLCM ) |
| EXIT; // repeated deallocation: just skip it. |
| |
| if( (flag == CV_GLCM_GLCM || flag == CV_GLCM_ALL) && (*GLCM)->matrices ) |
| { |
| for( matrixLoop = 0; matrixLoop < (*GLCM)->numMatrices; matrixLoop++ ) |
| { |
| if( (*GLCM)->matrices[ matrixLoop ] ) |
| { |
| cvFree( (*GLCM)->matrices[matrixLoop] ); |
| cvFree( (*GLCM)->matrices + matrixLoop ); |
| } |
| } |
| |
| cvFree( &((*GLCM)->matrices) ); |
| } |
| |
| if( (flag == CV_GLCM_DESC || flag == CV_GLCM_ALL) && (*GLCM)->descriptors ) |
| { |
| for( matrixLoop = 0; matrixLoop < (*GLCM)->numMatrices; matrixLoop++ ) |
| { |
| cvFree( (*GLCM)->descriptors + matrixLoop ); |
| } |
| cvFree( &((*GLCM)->descriptors) ); |
| } |
| |
| if( flag == CV_GLCM_ALL ) |
| { |
| cvFree( GLCM ); |
| } |
| |
| __END__; |
| } |
| |
| |
| static void |
| icvCreateGLCM_LookupTable_8u_C1R( const uchar* srcImageData, |
| int srcImageStep, |
| CvSize srcImageSize, |
| CvGLCM* destGLCM, |
| int* steps, |
| int numSteps, |
| int* memorySteps ) |
| { |
| int* stepIncrementsCounter = 0; |
| |
| CV_FUNCNAME( "icvCreateGLCM_LookupTable_8u_C1R" ); |
| |
| __BEGIN__; |
| |
| int matrixSideLength = destGLCM->matrixSideLength; |
| int stepLoop, sideLoop1, sideLoop2; |
| int colLoop, rowLoop, lineOffset = 0; |
| double*** matrices = 0; |
| |
| // allocate memory to the matrices |
| CV_CALL( destGLCM->matrices = (double***)cvAlloc( sizeof(matrices[0])*numSteps )); |
| matrices = destGLCM->matrices; |
| |
| for( stepLoop=0; stepLoop<numSteps; stepLoop++ ) |
| { |
| CV_CALL( matrices[stepLoop] = (double**)cvAlloc( sizeof(matrices[0])*matrixSideLength )); |
| CV_CALL( matrices[stepLoop][0] = (double*)cvAlloc( sizeof(matrices[0][0])* |
| matrixSideLength*matrixSideLength )); |
| |
| memset( matrices[stepLoop][0], 0, matrixSideLength*matrixSideLength* |
| sizeof(matrices[0][0]) ); |
| |
| for( sideLoop1 = 1; sideLoop1 < matrixSideLength; sideLoop1++ ) |
| { |
| matrices[stepLoop][sideLoop1] = matrices[stepLoop][sideLoop1-1] + matrixSideLength; |
| } |
| } |
| |
| CV_CALL( stepIncrementsCounter = (int*)cvAlloc( numSteps*sizeof(stepIncrementsCounter[0]))); |
| memset( stepIncrementsCounter, 0, numSteps*sizeof(stepIncrementsCounter[0]) ); |
| |
| // generate GLCM for each step |
| for( rowLoop=0; rowLoop<srcImageSize.height; rowLoop++, lineOffset+=srcImageStep ) |
| { |
| for( colLoop=0; colLoop<srcImageSize.width; colLoop++ ) |
| { |
| int pixelValue1 = destGLCM->forwardLookupTable[srcImageData[lineOffset + colLoop]]; |
| |
| for( stepLoop=0; stepLoop<numSteps; stepLoop++ ) |
| { |
| int col2, row2; |
| row2 = rowLoop + steps[stepLoop*2 + 0]; |
| col2 = colLoop + steps[stepLoop*2 + 1]; |
| |
| if( col2>=0 && row2>=0 && col2<srcImageSize.width && row2<srcImageSize.height ) |
| { |
| int memoryStep = memorySteps[ stepLoop ]; |
| int pixelValue2 = destGLCM->forwardLookupTable[ srcImageData[ lineOffset + colLoop + memoryStep ] ]; |
| |
| // maintain symmetry |
| matrices[stepLoop][pixelValue1][pixelValue2] ++; |
| matrices[stepLoop][pixelValue2][pixelValue1] ++; |
| |
| // incremenet counter of total number of increments |
| stepIncrementsCounter[stepLoop] += 2; |
| } |
| } |
| } |
| } |
| |
| // normalize matrices. each element is a probability of gray value i,j adjacency in direction/magnitude k |
| for( sideLoop1=0; sideLoop1<matrixSideLength; sideLoop1++ ) |
| { |
| for( sideLoop2=0; sideLoop2<matrixSideLength; sideLoop2++ ) |
| { |
| for( stepLoop=0; stepLoop<numSteps; stepLoop++ ) |
| { |
| matrices[stepLoop][sideLoop1][sideLoop2] /= double(stepIncrementsCounter[stepLoop]); |
| } |
| } |
| } |
| |
| destGLCM->matrices = matrices; |
| |
| __END__; |
| |
| cvFree( &stepIncrementsCounter ); |
| |
| if( cvGetErrStatus() < 0 ) |
| cvReleaseGLCM( &destGLCM, CV_GLCM_GLCM ); |
| } |
| |
| |
| CV_IMPL void |
| cvCreateGLCMDescriptors( CvGLCM* destGLCM, int descriptorOptimizationType ) |
| { |
| CV_FUNCNAME( "cvCreateGLCMDescriptors" ); |
| |
| __BEGIN__; |
| |
| int matrixLoop; |
| |
| if( !destGLCM ) |
| CV_ERROR( CV_StsNullPtr, "" ); |
| |
| if( !(destGLCM->matrices) ) |
| CV_ERROR( CV_StsNullPtr, "Matrices are not allocated" ); |
| |
| CV_CALL( cvReleaseGLCM( &destGLCM, CV_GLCM_DESC )); |
| |
| if( destGLCM->optimizationType != CV_GLCM_OPTIMIZATION_HISTOGRAM ) |
| { |
| destGLCM->descriptorOptimizationType = destGLCM->numDescriptors = descriptorOptimizationType; |
| } |
| else |
| { |
| CV_ERROR( CV_StsBadFlag, "Histogram-based method is not implemented" ); |
| // destGLCM->descriptorOptimizationType = destGLCM->numDescriptors = CV_GLCMDESC_OPTIMIZATION_HISTOGRAM; |
| } |
| |
| CV_CALL( destGLCM->descriptors = (double**) |
| cvAlloc( destGLCM->numMatrices*sizeof(destGLCM->descriptors[0]))); |
| |
| for( matrixLoop = 0; matrixLoop < destGLCM->numMatrices; matrixLoop ++ ) |
| { |
| CV_CALL( destGLCM->descriptors[ matrixLoop ] = |
| (double*)cvAlloc( destGLCM->numDescriptors*sizeof(destGLCM->descriptors[0][0]))); |
| memset( destGLCM->descriptors[matrixLoop], 0, destGLCM->numDescriptors*sizeof(double) ); |
| |
| switch( destGLCM->descriptorOptimizationType ) |
| { |
| case CV_GLCMDESC_OPTIMIZATION_ALLOWDOUBLENEST: |
| icvCreateGLCMDescriptors_AllowDoubleNest( destGLCM, matrixLoop ); |
| break; |
| default: |
| CV_ERROR( CV_StsBadFlag, |
| "descriptorOptimizationType different from CV_GLCMDESC_OPTIMIZATION_ALLOWDOUBLENEST\n" |
| "is not supported" ); |
| /* |
| case CV_GLCMDESC_OPTIMIZATION_ALLOWTRIPLENEST: |
| icvCreateGLCMDescriptors_AllowTripleNest( destGLCM, matrixLoop ); |
| break; |
| case CV_GLCMDESC_OPTIMIZATION_HISTOGRAM: |
| if(matrixLoop < destGLCM->numMatrices>>1) |
| icvCreateGLCMDescriptors_Histogram( destGLCM, matrixLoop); |
| break; |
| */ |
| } |
| } |
| |
| __END__; |
| |
| if( cvGetErrStatus() < 0 ) |
| cvReleaseGLCM( &destGLCM, CV_GLCM_DESC ); |
| } |
| |
| |
| static void |
| icvCreateGLCMDescriptors_AllowDoubleNest( CvGLCM* destGLCM, int matrixIndex ) |
| { |
| int sideLoop1, sideLoop2; |
| int matrixSideLength = destGLCM->matrixSideLength; |
| |
| double** matrix = destGLCM->matrices[ matrixIndex ]; |
| double* descriptors = destGLCM->descriptors[ matrixIndex ]; |
| |
| double* marginalProbability = |
| (double*)cvAlloc( matrixSideLength * sizeof(marginalProbability[0])); |
| memset( marginalProbability, 0, matrixSideLength * sizeof(double) ); |
| |
| double maximumProbability = 0; |
| double marginalProbabilityEntropy = 0; |
| double correlationMean = 0, correlationStdDeviation = 0, correlationProductTerm = 0; |
| |
| for( sideLoop1=0; sideLoop1<matrixSideLength; sideLoop1++ ) |
| { |
| int actualSideLoop1 = destGLCM->reverseLookupTable[ sideLoop1 ]; |
| |
| for( sideLoop2=0; sideLoop2<matrixSideLength; sideLoop2++ ) |
| { |
| double entryValue = matrix[ sideLoop1 ][ sideLoop2 ]; |
| |
| int actualSideLoop2 = destGLCM->reverseLookupTable[ sideLoop2 ]; |
| int sideLoopDifference = actualSideLoop1 - actualSideLoop2; |
| int sideLoopDifferenceSquared = sideLoopDifference*sideLoopDifference; |
| |
| marginalProbability[ sideLoop1 ] += entryValue; |
| correlationMean += actualSideLoop1*entryValue; |
| |
| maximumProbability = MAX( maximumProbability, entryValue ); |
| |
| if( actualSideLoop2 > actualSideLoop1 ) |
| { |
| descriptors[ CV_GLCMDESC_CONTRAST ] += sideLoopDifferenceSquared * entryValue; |
| } |
| |
| descriptors[ CV_GLCMDESC_HOMOGENITY ] += entryValue / ( 1.0 + sideLoopDifferenceSquared ); |
| |
| if( entryValue > 0 ) |
| { |
| descriptors[ CV_GLCMDESC_ENTROPY ] += entryValue * log( entryValue ); |
| } |
| |
| descriptors[ CV_GLCMDESC_ENERGY ] += entryValue*entryValue; |
| } |
| |
| if( marginalProbability ) |
| marginalProbabilityEntropy += marginalProbability[ actualSideLoop1 ]*log(marginalProbability[ actualSideLoop1 ]); |
| } |
| |
| marginalProbabilityEntropy = -marginalProbabilityEntropy; |
| |
| descriptors[ CV_GLCMDESC_CONTRAST ] += descriptors[ CV_GLCMDESC_CONTRAST ]; |
| descriptors[ CV_GLCMDESC_ENTROPY ] = -descriptors[ CV_GLCMDESC_ENTROPY ]; |
| descriptors[ CV_GLCMDESC_MAXIMUMPROBABILITY ] = maximumProbability; |
| |
| double HXY = 0, HXY1 = 0, HXY2 = 0; |
| |
| HXY = descriptors[ CV_GLCMDESC_ENTROPY ]; |
| |
| for( sideLoop1=0; sideLoop1<matrixSideLength; sideLoop1++ ) |
| { |
| double sideEntryValueSum = 0; |
| int actualSideLoop1 = destGLCM->reverseLookupTable[ sideLoop1 ]; |
| |
| for( sideLoop2=0; sideLoop2<matrixSideLength; sideLoop2++ ) |
| { |
| double entryValue = matrix[ sideLoop1 ][ sideLoop2 ]; |
| |
| sideEntryValueSum += entryValue; |
| |
| int actualSideLoop2 = destGLCM->reverseLookupTable[ sideLoop2 ]; |
| |
| correlationProductTerm += (actualSideLoop1 - correlationMean) * (actualSideLoop2 - correlationMean) * entryValue; |
| |
| double clusterTerm = actualSideLoop1 + actualSideLoop2 - correlationMean - correlationMean; |
| |
| descriptors[ CV_GLCMDESC_CLUSTERTENDENCY ] += clusterTerm * clusterTerm * entryValue; |
| descriptors[ CV_GLCMDESC_CLUSTERSHADE ] += clusterTerm * clusterTerm * clusterTerm * entryValue; |
| |
| double HXYValue = marginalProbability[ actualSideLoop1 ] * marginalProbability[ actualSideLoop2 ]; |
| if( HXYValue>0 ) |
| { |
| double HXYValueLog = log( HXYValue ); |
| HXY1 += entryValue * HXYValueLog; |
| HXY2 += HXYValue * HXYValueLog; |
| } |
| } |
| |
| correlationStdDeviation += (actualSideLoop1-correlationMean) * (actualSideLoop1-correlationMean) * sideEntryValueSum; |
| } |
| |
| HXY1 = -HXY1; |
| HXY2 = -HXY2; |
| |
| descriptors[ CV_GLCMDESC_CORRELATIONINFO1 ] = ( HXY - HXY1 ) / ( correlationMean ); |
| descriptors[ CV_GLCMDESC_CORRELATIONINFO2 ] = sqrt( 1.0 - exp( -2.0 * (HXY2 - HXY ) ) ); |
| |
| correlationStdDeviation = sqrt( correlationStdDeviation ); |
| |
| descriptors[ CV_GLCMDESC_CORRELATION ] = correlationProductTerm / (correlationStdDeviation*correlationStdDeviation ); |
| |
| delete [] marginalProbability; |
| } |
| |
| |
| CV_IMPL double cvGetGLCMDescriptor( CvGLCM* GLCM, int step, int descriptor ) |
| { |
| double value = DBL_MAX; |
| |
| CV_FUNCNAME( "cvGetGLCMDescriptor" ); |
| |
| __BEGIN__; |
| |
| if( !GLCM ) |
| CV_ERROR( CV_StsNullPtr, "" ); |
| |
| if( !(GLCM->descriptors) ) |
| CV_ERROR( CV_StsNullPtr, "" ); |
| |
| if( (unsigned)step >= (unsigned)(GLCM->numMatrices)) |
| CV_ERROR( CV_StsOutOfRange, "step is not in 0 .. GLCM->numMatrices - 1" ); |
| |
| if( (unsigned)descriptor >= (unsigned)(GLCM->numDescriptors)) |
| CV_ERROR( CV_StsOutOfRange, "descriptor is not in 0 .. GLCM->numDescriptors - 1" ); |
| |
| value = GLCM->descriptors[step][descriptor]; |
| |
| __END__; |
| |
| return value; |
| } |
| |
| |
| CV_IMPL void |
| cvGetGLCMDescriptorStatistics( CvGLCM* GLCM, int descriptor, |
| double* _average, double* _standardDeviation ) |
| { |
| CV_FUNCNAME( "cvGetGLCMDescriptorStatistics" ); |
| |
| if( _average ) |
| *_average = DBL_MAX; |
| |
| if( _standardDeviation ) |
| *_standardDeviation = DBL_MAX; |
| |
| __BEGIN__; |
| |
| int matrixLoop, numMatrices; |
| double average = 0, squareSum = 0; |
| |
| if( !GLCM ) |
| CV_ERROR( CV_StsNullPtr, "" ); |
| |
| if( !(GLCM->descriptors)) |
| CV_ERROR( CV_StsNullPtr, "Descriptors are not calculated" ); |
| |
| if( (unsigned)descriptor >= (unsigned)(GLCM->numDescriptors) ) |
| CV_ERROR( CV_StsOutOfRange, "Descriptor index is out of range" ); |
| |
| numMatrices = GLCM->numMatrices; |
| |
| for( matrixLoop = 0; matrixLoop < numMatrices; matrixLoop++ ) |
| { |
| double temp = GLCM->descriptors[ matrixLoop ][ descriptor ]; |
| average += temp; |
| squareSum += temp*temp; |
| } |
| |
| average /= numMatrices; |
| |
| if( _average ) |
| *_average = average; |
| |
| if( _standardDeviation ) |
| *_standardDeviation = sqrt( (squareSum - average*average*numMatrices)/(numMatrices-1)); |
| |
| __END__; |
| } |
| |
| |
| CV_IMPL IplImage* |
| cvCreateGLCMImage( CvGLCM* GLCM, int step ) |
| { |
| IplImage* dest = 0; |
| |
| CV_FUNCNAME( "cvCreateGLCMImage" ); |
| |
| __BEGIN__; |
| |
| float* destData; |
| int sideLoop1, sideLoop2; |
| |
| if( !GLCM ) |
| CV_ERROR( CV_StsNullPtr, "" ); |
| |
| if( !(GLCM->matrices) ) |
| CV_ERROR( CV_StsNullPtr, "Matrices are not allocated" ); |
| |
| if( (unsigned)step >= (unsigned)(GLCM->numMatrices) ) |
| CV_ERROR( CV_StsOutOfRange, "The step index is out of range" ); |
| |
| dest = cvCreateImage( cvSize( GLCM->matrixSideLength, GLCM->matrixSideLength ), IPL_DEPTH_32F, 1 ); |
| destData = (float*)(dest->imageData); |
| |
| for( sideLoop1 = 0; sideLoop1 < GLCM->matrixSideLength; |
| sideLoop1++, (float*&)destData += dest->widthStep ) |
| { |
| for( sideLoop2=0; sideLoop2 < GLCM->matrixSideLength; sideLoop2++ ) |
| { |
| double matrixValue = GLCM->matrices[step][sideLoop1][sideLoop2]; |
| destData[ sideLoop2 ] = (float)matrixValue; |
| } |
| } |
| |
| __END__; |
| |
| if( cvGetErrStatus() < 0 ) |
| cvReleaseImage( &dest ); |
| |
| return dest; |
| } |
| |
