cvsumpixels.cpp.svn-base
来自「非结构化路识别」· SVN-BASE 代码 · 共 803 行 · 第 1/3 页
SVN-BASE
803 行
memset( sqsum, 0, (size.width+1)*sizeof(sqsum[0])); \
sqsumstep /= sizeof(sqsum[0]); \
sqsum += sqsumstep + 1; \
} \
\
if( tilted ) \
{ \
memset( tilted, 0, (size.width+1)*sizeof(tilted[0])); \
tiltedstep /= sizeof(tilted[0]); \
tilted += tiltedstep + 1; \
} \
\
if( sqsum == 0 && tilted == 0 ) \
{ \
sum[-1] = 0; \
for( x = 0, s = 0; x < size.width; x++ ) \
{ \
sumtype t = cast_macro(src[x]); \
sum[x] = (s += t); \
} \
\
for( y = 1; y < size.height; y++ ) \
{ \
src += srcstep; \
sum += sumstep; \
sum[-1] = 0; \
\
for( x = 0, s = 0; x < size.width; x++ ) \
{ \
sumtype t = cast_macro(src[x]); \
s += t; \
sum[x] = sum[x - sumstep] + s; \
} \
} \
} \
else if( tilted == 0 ) \
{ \
sum[-1] = 0; \
sqsum[-1] = 0; \
\
for( x = 0, s = 0, sq = 0; x < size.width; x++ ) \
{ \
worktype it = src[x]; \
sumtype t = cast_macro(it); \
sqsumtype tq = cast_sqr_macro(it); \
s += t; \
sq += tq; \
sum[x] = s; \
sqsum[x] = sq; \
} \
\
for( y = 1; y < size.height; y++ ) \
{ \
src += srcstep; \
sum += sumstep; \
sqsum += sqsumstep; \
\
sum[-1] = 0; \
sqsum[-1] = 0; \
\
for( x = 0, s = 0, sq = 0; x < size.width; x++ ) \
{ \
worktype it = src[x]; \
sumtype t = cast_macro(it); \
sqsumtype tq = cast_sqr_macro(it); \
s += t; \
sq += tq; \
t = sum[x - sumstep] + s; \
tq = sqsum[x - sqsumstep] + sq; \
sum[x] = t; \
sqsum[x] = tq; \
} \
} \
} \
else \
{ \
if( sqsum == 0 ) \
{ \
assert(0); \
return CV_NULLPTR_ERR; \
} \
\
buf = (sumtype*)alloca( (size.width + 1 )* sizeof(buf[0])); \
sum[-1] = tilted[-1] = 0; \
sqsum[-1] = 0; \
\
for( x = 0, s = 0, sq = 0; x < size.width; x++ ) \
{ \
worktype it = src[x]; \
sumtype t = cast_macro(it); \
sqsumtype tq = cast_sqr_macro(it); \
buf[x] = tilted[x] = t; \
s += t; \
sq += tq; \
sum[x] = s; \
sqsum[x] = sq; \
} \
\
if( size.width == 1 ) \
buf[1] = 0; \
\
for( y = 1; y < size.height; y++ ) \
{ \
worktype it; \
sumtype t0; \
sqsumtype tq0; \
\
src += srcstep; \
sum += sumstep; \
sqsum += sqsumstep; \
tilted += tiltedstep; \
\
it = src[0/*x*/]; \
s = t0 = cast_macro(it); \
sq = tq0 = cast_sqr_macro(it); \
\
sum[-1] = 0; \
sqsum[-1] = 0; \
/*tilted[-1] = buf[0];*/ \
tilted[-1] = tilted[-tiltedstep]; \
\
sum[0] = sum[-sumstep] + t0; \
sqsum[0] = sqsum[-sqsumstep] + tq0; \
tilted[0] = tilted[-tiltedstep] + t0 + buf[1]; \
\
for( x = 1; x < size.width - 1; x++ ) \
{ \
sumtype t1 = buf[x]; \
buf[x-1] = t1 + t0; \
it = src[x]; \
t0 = cast_macro(it); \
tq0 = cast_sqr_macro(it); \
s += t0; \
sq += tq0; \
sum[x] = sum[x - sumstep] + s; \
sqsum[x] = sqsum[x - sqsumstep] + sq; \
t1 += buf[x+1] + t0 + tilted[x - tiltedstep - 1]; \
tilted[x] = t1; \
} \
\
if( size.width > 1 ) \
{ \
sumtype t1 = buf[x]; \
buf[x-1] = t1 + t0; \
it = src[x]; /*+*/ \
t0 = cast_macro(it); \
tq0 = cast_sqr_macro(it); \
s += t0; \
sq += tq0; \
sum[x] = sum[x - sumstep] + s; \
sqsum[x] = sqsum[x - sqsumstep] + sq; \
tilted[x] = t0 + t1 + tilted[x - tiltedstep - 1]; \
buf[x] = t0; \
} \
} \
} \
\
return CV_OK; \
}
ICV_DEF_INTEGRAL_OP( 8u32s, uchar, int, double, int, CV_NOP, CV_8TO32F_SQR )
ICV_DEF_INTEGRAL_OP( 8u64f, uchar, double, double, int, CV_8TO32F, CV_8TO32F_SQR )
ICV_DEF_INTEGRAL_OP( 32f64f, float, double, double, double, CV_NOP, CV_SQR )
ICV_DEF_INTEGRAL_OP( 64f, double, double, double, double, CV_NOP, CV_SQR )
static void icvInitIntegralImageTable( CvFuncTable* table )
{
table->fn_2d[CV_8U] = (void*)icvIntegralImage_8u64f_C1R;
table->fn_2d[CV_32F] = (void*)icvIntegralImage_32f64f_C1R;
table->fn_2d[CV_64F] = (void*)icvIntegralImage_64f_C1R;
}
typedef CvStatus (CV_STDCALL * CvIntegralImageFunc)( const void* src, int srcstep,
void* sum, int sumstep,
void* sqsum, int sqsumstep,
void* tilted, int tiltedstep,
CvSize size );
CV_IMPL void
cvIntegral( const CvArr* image, CvArr* sumImage,
CvArr* sumSqImage, CvArr* tiltedSumImage )
{
static CvFuncTable tab;
static int inittab = 0;
CV_FUNCNAME( "cvIntegralImage" );
__BEGIN__;
CvMat src_stub, *src = (CvMat*)image;
CvMat sum_stub, *sum = (CvMat*)sumImage;
CvMat sqsum_stub, *sqsum = (CvMat*)sumSqImage;
CvMat tilted_stub, *tilted = (CvMat*)tiltedSumImage;
int coi0 = 0, coi1 = 0, coi2 = 0, coi3 = 0;
CvIntegralImageFunc func = 0;
if( !inittab )
{
icvInitIntegralImageTable( &tab );
inittab = 1;
}
CV_CALL( src = cvGetMat( src, &src_stub, &coi0 ));
CV_CALL( sum = cvGetMat( sum, &sum_stub, &coi1 ));
if( sum->width != src->width + 1 ||
sum->height != src->height + 1 )
CV_ERROR( CV_StsUnmatchedSizes, "" );
if( CV_MAT_TYPE( sum->type ) != CV_64FC1 &&
(CV_MAT_TYPE( src->type ) != CV_8UC1 ||
CV_MAT_TYPE( sum->type ) != CV_32SC1))
CV_ERROR( CV_StsUnsupportedFormat,
"Sum array must be single-channel and have 64f "
"(or 32s in case of 8u source array) type" );
if( sqsum )
{
CV_CALL( sqsum = cvGetMat( sqsum, &sqsum_stub, &coi2 ));
if( !CV_ARE_SIZES_EQ( sum, sqsum ) )
CV_ERROR( CV_StsUnmatchedSizes, "" );
if( CV_MAT_TYPE( sqsum->type ) != CV_64FC1 )
CV_ERROR( CV_StsUnsupportedFormat,
"Squares sum array must be 64f,single-channel" );
}
if( tilted )
{
if( !sqsum )
CV_ERROR( CV_StsNullPtr,
"Squared sum array must be passed if tilted sum array is passed" );
CV_CALL( tilted = cvGetMat( tilted, &tilted_stub, &coi3 ));
if( !CV_ARE_SIZES_EQ( sum, tilted ) )
CV_ERROR( CV_StsUnmatchedSizes, "" );
if( !CV_ARE_TYPES_EQ( sum, tilted ) )
CV_ERROR( CV_StsUnmatchedFormats,
"Sum and tilted sum must have the same types" );
}
if( coi0 || coi1 || coi2 || coi3 )
CV_ERROR( CV_BadCOI, "COI is not supported by the function" );
if( CV_MAT_TYPE( sum->type ) == CV_32SC1 )
func = (CvIntegralImageFunc)icvIntegralImage_8u32s_C1R;
else
{
func = (CvIntegralImageFunc)tab.fn_2d[CV_MAT_DEPTH(src->type)];
if( !func )
CV_ERROR( CV_StsUnsupportedFormat, "This source image format is unsupported" );
}
IPPI_CALL( func( src->data.ptr, src->step, sum->data.ptr, sum->step,
sqsum ? sqsum->data.ptr : 0, sqsum ? sqsum->step : 0,
tilted ? tilted->data.ptr : 0, tilted ? tilted->step : 0,
icvGetMatSize( src )));
__END__;
}
/* End of file. */
⌨️ 快捷键说明
复制代码Ctrl + C
搜索代码Ctrl + F
全屏模式F11
增大字号Ctrl + =
减小字号Ctrl + -
显示快捷键?