static void
cvTsCalcBackProject( IplImage** images, IplImage* dst, CvHistogram* hist, int* channels )
{
int x, y, k, cdims;
union
{
float* fl;
uchar* ptr;
}
plane[CV_MAX_DIM];
int nch[CV_MAX_DIM];
int dims[CV_MAX_DIM];
int uniform = CV_IS_UNIFORM_HIST(hist);
CvSize img_size = cvGetSize(images[0]);
int img_depth = images[0]->depth;
cdims = cvGetDims( hist->bins, dims );
for( k = 0; k < cdims; k++ )
nch[k] = images[k]->nChannels;
for( y = 0; y < img_size.height; y++ )
{
if( img_depth == IPL_DEPTH_8U )
for( k = 0; k < cdims; k++ )
plane[k].ptr = &CV_IMAGE_ELEM(images[k], uchar, y, 0 ) + channels[k];
else
for( k = 0; k < cdims; k++ )
plane[k].fl = &CV_IMAGE_ELEM(images[k], float, y, 0 ) + channels[k];
for( x = 0; x < img_size.width; x++ )
{
float val[CV_MAX_DIM];
float bin_val = 0;
int idx[CV_MAX_DIM];
if( img_depth == IPL_DEPTH_8U )
for( k = 0; k < cdims; k++ )
val[k] = plane[k].ptr[x*nch[k]];
else
for( k = 0; k < cdims; k++ )
val[k] = plane[k].fl[x*nch[k]];
idx[cdims-1] = -1;
if( uniform )
{
for( k = 0; k < cdims; k++ )
{
double v = val[k], lo = hist->thresh[k][0], hi = hist->thresh[k][1];
idx[k] = cvFloor((v - lo)*dims[k]/(hi - lo));
if( idx[k] < 0 || idx[k] >= dims[k] )
break;
}
}
else
{
for( k = 0; k < cdims; k++ )
{
float v = val[k];
float* t = hist->thresh2[k];
int j, n = dims[k];
for( j = 0; j <= n; j++ )
if( v < t[j] )
break;
if( j <= 0 || j > n )
break;
idx[k] = j-1;
}
}
if( k == cdims )
bin_val = (float)cvGetRealND( hist->bins, idx );
if( img_depth == IPL_DEPTH_8U )
{
int t = cvRound(bin_val);
CV_IMAGE_ELEM( dst, uchar, y, x ) = CV_CAST_8U(t);
}
else
CV_IMAGE_ELEM( dst, float, y, x ) = bin_val;
}
}
}
static double
icvGetThreshVal_Otsu( const CvHistogram* hist )
{
double max_val = 0;
CV_FUNCNAME( "icvGetThreshVal_Otsu" );
__BEGIN__;
int i, count;
const float* h;
double sum = 0, mu = 0;
bool uniform = false;
double low = 0, high = 0, delta = 0;
float* nu_thresh = 0;
double mu1 = 0, q1 = 0;
double max_sigma = 0;
if( !CV_IS_HIST(hist) || CV_IS_SPARSE_HIST(hist) || hist->mat.dims != 1 )
CV_ERROR( CV_StsBadArg,
"The histogram in Otsu method must be a valid dense 1D histogram" );
count = hist->mat.dim[0].size;
h = (float*)cvPtr1D( hist->bins, 0 );
if( !CV_HIST_HAS_RANGES(hist) || CV_IS_UNIFORM_HIST(hist) )
{
if( CV_HIST_HAS_RANGES(hist) )
{
low = hist->thresh[0][0];
high = hist->thresh[0][1];
}
else
{
low = 0;
high = count;
}
delta = (high-low)/count;
low += delta*0.5;
uniform = true;
}
else
nu_thresh = hist->thresh2[0];
for( i = 0; i < count; i++ )
{
sum += h[i];
if( uniform )
mu += (i*delta + low)*h[i];
else
mu += (nu_thresh[i*2] + nu_thresh[i*2+1])*0.5*h[i];
}
sum = fabs(sum) > FLT_EPSILON ? 1./sum : 0;
mu *= sum;
mu1 = 0;
q1 = 0;
for( i = 0; i < count; i++ )
{
double p_i, q2, mu2, val_i, sigma;
p_i = h[i]*sum;
mu1 *= q1;
q1 += p_i;
q2 = 1. - q1;
if( MIN(q1,q2) < FLT_EPSILON || MAX(q1,q2) > 1. - FLT_EPSILON )
continue;
if( uniform )
val_i = i*delta + low;
else
val_i = (nu_thresh[i*2] + nu_thresh[i*2+1])*0.5;
mu1 = (mu1 + val_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 = val_i;
}
}
__END__;
return max_val;
}
static void
cvTsCalcHist( IplImage** _images, CvHistogram* hist, IplImage* _mask, int* channels )
{
int x, y, k, cdims;
union
{
float* fl;
uchar* ptr;
}
plane[CV_MAX_DIM];
int nch[CV_MAX_DIM];
int dims[CV_MAX_DIM];
int uniform = CV_IS_UNIFORM_HIST(hist);
CvSize img_size = cvGetSize(_images[0]);
CvMat images[CV_MAX_DIM], mask = cvMat(1,1,CV_8U);
int img_depth = _images[0]->depth;
cdims = cvGetDims( hist->bins, dims );
cvZero( hist->bins );
for( k = 0; k < cdims; k++ )
{
cvGetMat( _images[k], &images[k] );
nch[k] = _images[k]->nChannels;
}
if( _mask )
cvGetMat( _mask, &mask );
for( y = 0; y < img_size.height; y++ )
{
const uchar* mptr = _mask ? &CV_MAT_ELEM(mask, uchar, y, 0 ) : 0;
if( img_depth == IPL_DEPTH_8U )
for( k = 0; k < cdims; k++ )
plane[k].ptr = &CV_MAT_ELEM(images[k], uchar, y, 0 ) + channels[k];
else
for( k = 0; k < cdims; k++ )
plane[k].fl = &CV_MAT_ELEM(images[k], float, y, 0 ) + channels[k];
for( x = 0; x < img_size.width; x++ )
{
float val[CV_MAX_DIM];
int idx[CV_MAX_DIM];
if( mptr && !mptr[x] )
continue;
if( img_depth == IPL_DEPTH_8U )
for( k = 0; k < cdims; k++ )
val[k] = plane[k].ptr[x*nch[k]];
else
for( k = 0; k < cdims; k++ )
val[k] = plane[k].fl[x*nch[k]];
idx[cdims-1] = -1;
if( uniform )
{
for( k = 0; k < cdims; k++ )
{
double v = val[k], lo = hist->thresh[k][0], hi = hist->thresh[k][1];
idx[k] = cvFloor((v - lo)*dims[k]/(hi - lo));
if( idx[k] < 0 || idx[k] >= dims[k] )
break;
}
}
else
{
for( k = 0; k < cdims; k++ )
{
float v = val[k];
float* t = hist->thresh2[k];
int j, n = dims[k];
for( j = 0; j <= n; j++ )
if( v < t[j] )
break;
if( j <= 0 || j > n )
break;
idx[k] = j-1;
}
}
if( k < cdims )
continue;
(*(float*)cvPtrND( hist->bins, idx ))++;
}
}
}
