Add template match with mask.

Signed-off-by: Yan Wang <yan.wang@linux.intel.com>
This commit is contained in:
Yan Wang 2014-12-24 14:02:53 +08:00
parent 61991a3330
commit 46ed461e22
6 changed files with 161 additions and 2 deletions

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@ -3330,9 +3330,11 @@ data type.
@param result Map of comparison results. It must be single-channel 32-bit floating-point. If image @param result Map of comparison results. It must be single-channel 32-bit floating-point. If image
is \f$W \times H\f$ and templ is \f$w \times h\f$ , then result is \f$(W-w+1) \times (H-h+1)\f$ . is \f$W \times H\f$ and templ is \f$w \times h\f$ , then result is \f$(W-w+1) \times (H-h+1)\f$ .
@param method Parameter specifying the comparison method, see cv::TemplateMatchModes @param method Parameter specifying the comparison method, see cv::TemplateMatchModes
@param mask Mask of searched template. It must have the same datatype and size with templ. It is
not set by default.
*/ */
CV_EXPORTS_W void matchTemplate( InputArray image, InputArray templ, CV_EXPORTS_W void matchTemplate( InputArray image, InputArray templ,
OutputArray result, int method ); OutputArray result, int method, InputArray mask = noArray() );
//! @} //! @}

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@ -814,12 +814,97 @@ void crossCorr( const Mat& img, const Mat& _templ, Mat& corr,
} }
} }
} }
static void matchTemplateMask( InputArray _img, InputArray _templ, OutputArray _result, int method, InputArray _mask )
{
int type = _img.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
CV_Assert( CV_TM_SQDIFF <= method && method <= CV_TM_CCOEFF_NORMED );
CV_Assert( (depth == CV_8U || depth == CV_32F) && type == _templ.type() && _img.dims() <= 2 );
Mat img = _img.getMat(), templ = _templ.getMat(), mask = _mask.getMat();
int ttype = templ.type(), tdepth = CV_MAT_DEPTH(ttype), tcn = CV_MAT_CN(ttype);
int mtype = img.type(), mdepth = CV_MAT_DEPTH(type), mcn = CV_MAT_CN(mtype);
if (depth == CV_8U)
{
depth = CV_32F;
type = CV_MAKETYPE(CV_32F, cn);
img.convertTo(img, type, 1.0 / 255);
}
if (tdepth == CV_8U)
{
tdepth = CV_32F;
ttype = CV_MAKETYPE(CV_32F, tcn);
templ.convertTo(templ, ttype, 1.0 / 255);
}
if (mdepth == CV_8U)
{
mdepth = CV_32F;
mtype = CV_MAKETYPE(CV_32F, mcn);
compare(mask, Scalar::all(0), mask, CMP_NE);
mask.convertTo(mask, mtype, 1.0 / 255);
}
Size corrSize(img.cols - templ.cols + 1, img.rows - templ.rows + 1);
_result.create(corrSize, CV_32F);
Mat result = _result.getMat();
Mat img2 = img.mul(img);
Mat mask2 = mask.mul(mask);
Mat mask_templ = templ.mul(mask);
Scalar templMean, templSdv;
double templSum2 = 0;
meanStdDev( mask_templ, templMean, templSdv );
templSum2 = templSdv[0]*templSdv[0] + templSdv[1]*templSdv[1] + templSdv[2]*templSdv[2] + templSdv[3]*templSdv[3];
templSum2 += templMean[0]*templMean[0] + templMean[1]*templMean[1] + templMean[2]*templMean[2] + templMean[3]*templMean[3];
templSum2 *= ((double)templ.rows * templ.cols);
if (method == CV_TM_SQDIFF)
{
Mat mask2_templ = templ.mul(mask2);
Mat corr(corrSize, CV_32F);
crossCorr( img, mask2_templ, corr, corr.size(), corr.type(), Point(0,0), 0, 0 );
crossCorr( img2, mask, result, result.size(), result.type(), Point(0,0), 0, 0 );
result -= corr * 2;
result += templSum2;
}
else if (method == CV_TM_CCORR_NORMED)
{
if (templSum2 < DBL_EPSILON)
{
result = Scalar::all(1);
return;
}
Mat corr(corrSize, CV_32F);
crossCorr( img2, mask2, corr, corr.size(), corr.type(), Point(0,0), 0, 0 );
crossCorr( img, mask_templ, result, result.size(), result.type(), Point(0,0), 0, 0 );
sqrt(corr, corr);
result = result.mul(1/corr);
result /= std::sqrt(templSum2);
}
else
CV_Error(Error::StsNotImplemented, "");
}
} }
//////////////////////////////////////////////////////////////////////////////////////////////////////// ////////////////////////////////////////////////////////////////////////////////////////////////////////
void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result, int method ) void cv::matchTemplate( InputArray _img, InputArray _templ, OutputArray _result, int method, InputArray _mask )
{ {
if (!_mask.empty())
{
cv::matchTemplateMask(_img, _templ, _result, method, _mask);
return;
}
int type = _img.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type); int type = _img.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
CV_Assert( CV_TM_SQDIFF <= method && method <= CV_TM_CCOEFF_NORMED ); CV_Assert( CV_TM_SQDIFF <= method && method <= CV_TM_CCOEFF_NORMED );
CV_Assert( (depth == CV_8U || depth == CV_32F) && type == _templ.type() && _img.dims() <= 2 ); CV_Assert( (depth == CV_8U || depth == CV_32F) && type == _templ.type() && _img.dims() <= 2 );

72
samples/cpp/mask_tmpl.cpp Normal file
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@ -0,0 +1,72 @@
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
#include <cctype>
#include <iostream>
#include <iterator>
#include <stdio.h>
using namespace std;
using namespace cv;
static void help()
{
cout << "\nThis program demonstrates template match with mask.\n"
"Usage:\n"
"./mask_tmpl <image_name> <template_name> <mask_name>, Default is ../data/lena_tmpl.jpg\n"
<< endl;
}
int main( int argc, const char** argv )
{
const char* filename = argc == 4 ? argv[1] : "../data/lena_tmpl.jpg";
const char* tmplname = argc == 4 ? argv[2] : "../data/tmpl.png";
const char* maskname = argc == 4 ? argv[3] : "../data/mask.png";
Mat img = imread(filename);
Mat tmpl = imread(tmplname);
Mat mask = imread(maskname);
Mat res;
if(img.empty())
{
help();
cout << "can not open " << filename << endl;
return -1;
}
if(tmpl.empty())
{
help();
cout << "can not open " << tmplname << endl;
return -1;
}
if(mask.empty())
{
help();
cout << "can not open " << maskname << endl;
return -1;
}
//int method = CV_TM_SQDIFF;
int method = CV_TM_CCORR_NORMED;
matchTemplate(img, tmpl, res, method, mask);
double minVal, maxVal;
Point minLoc, maxLoc;
Rect rect;
minMaxLoc(res, &minVal, &maxVal, &minLoc, &maxLoc);
if(method == CV_TM_SQDIFF || method == CV_TM_SQDIFF_NORMED)
rect = Rect(minLoc, tmpl.size());
else
rect = Rect(maxLoc, tmpl.size());
rectangle(img, rect, Scalar(0, 255, 0), 2);
imshow("detected template", img);
waitKey();
return 0;
}

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