diff --git a/modules/imgproc/src/templmatch.cpp b/modules/imgproc/src/templmatch.cpp
index 38b4f62928..57d7701e5e 100644
--- a/modules/imgproc/src/templmatch.cpp
+++ b/modules/imgproc/src/templmatch.cpp
@@ -41,429 +41,320 @@
 
 #include "precomp.hpp"
 
-void
-icvCrossCorr( const CvArr* _img, const CvArr* _templ, CvArr* _corr,
-              CvPoint anchor, double delta, int borderType )
+namespace cv
 {
-    const int CV_MAX_THREADS = 1;
-    const double block_scale = 4.5;
-    const int min_block_size = 256;
-    cv::Ptr<CvMat> dft_img[CV_MAX_THREADS];
-    cv::Ptr<CvMat> dft_templ;
-    std::vector<uchar> buf[CV_MAX_THREADS];
-    int k, num_threads = 0;
+
+void crossCorr( const Mat& img, const Mat& templ, Mat& corr,
+                Size corrsize, int ctype,
+                Point anchor, double delta, int borderType )
+{
+    const double blockScale = 4.5;
+    const int minBlockSize = 256;
+    std::vector<uchar> buf;
+
+    int depth = img.depth(), cn = img.channels();
+    int tdepth = templ.depth(), tcn = templ.channels();
+    int cdepth = CV_MAT_DEPTH(ctype), ccn = CV_MAT_CN(ctype);
     
-    CvMat istub, *img = (CvMat*)_img;
-    CvMat tstub, *templ = (CvMat*)_templ;
-    CvMat cstub, *corr = (CvMat*)_corr;
-    CvSize dftsize, blocksize;
-    int depth, templ_depth, corr_depth, max_depth = CV_32F,
-        cn, templ_cn, corr_cn, buf_size = 0,
-        tile_count_x, tile_count_y, tile_count;
-
-    img = cvGetMat( img, &istub );
-    templ = cvGetMat( templ, &tstub );
-    corr = cvGetMat( corr, &cstub );
-
-    if( CV_MAT_DEPTH( img->type ) != CV_8U &&
-        CV_MAT_DEPTH( img->type ) != CV_16U &&
-        CV_MAT_DEPTH( img->type ) != CV_32F &&
-        CV_MAT_DEPTH( img->type ) != CV_64F )
-        CV_Error( CV_StsUnsupportedFormat,
-        "The function supports only 8u, 16u and 32f data types" );
-
-    if( !CV_ARE_DEPTHS_EQ( img, templ ) && CV_MAT_DEPTH( templ->type ) != CV_32F )
-        CV_Error( CV_StsUnsupportedFormat,
-        "Template (kernel) must be of the same depth as the input image, or be 32f" );
+    CV_Assert( img.dims <= 2 && templ.dims <= 2 && corr.dims <= 2 );
+    CV_Assert( depth == CV_8U || depth == CV_16U || depth == CV_32F || depth == CV_64F );
+    CV_Assert( depth == tdepth || tdepth == CV_32F );
     
-    if( !CV_ARE_DEPTHS_EQ( img, corr ) && CV_MAT_DEPTH( corr->type ) != CV_32F &&
-        CV_MAT_DEPTH( corr->type ) != CV_64F )
-        CV_Error( CV_StsUnsupportedFormat,
-        "The output image must have the same depth as the input image, or be 32f/64f" );
+    CV_Assert( corrsize.height <= img.rows + templ.rows - 1 &&
+               corrsize.width <= img.cols + templ.cols - 1 );
+    
+    CV_Assert( ccn == 1 || delta == 0 );
+    
+    corr.create(corrsize, ctype);
 
-    if( (!CV_ARE_CNS_EQ( img, corr ) || CV_MAT_CN(templ->type) > 1) &&
-        (CV_MAT_CN( corr->type ) > 1 || !CV_ARE_CNS_EQ( img, templ)) )
-        CV_Error( CV_StsUnsupportedFormat,
-        "The output must have the same number of channels as the input (when the template has 1 channel), "
-        "or the output must have 1 channel when the input and the template have the same number of channels" );
+    int maxDepth = depth > CV_8U ? CV_64F : std::max(std::max(CV_32F, tdepth), cdepth);
+    Size blocksize, dftsize;
+    
+    blocksize.width = cvRound(templ.cols*blockScale);
+    blocksize.width = std::max( blocksize.width, minBlockSize - templ.cols + 1 );
+    blocksize.width = std::min( blocksize.width, corr.cols );
+    blocksize.height = cvRound(templ.rows*blockScale);
+    blocksize.height = std::max( blocksize.height, minBlockSize - templ.rows + 1 );
+    blocksize.height = std::min( blocksize.height, corr.rows );
 
-    depth = CV_MAT_DEPTH(img->type);
-    cn = CV_MAT_CN(img->type);
-    templ_depth = CV_MAT_DEPTH(templ->type);
-    templ_cn = CV_MAT_CN(templ->type);
-    corr_depth = CV_MAT_DEPTH(corr->type);
-    corr_cn = CV_MAT_CN(corr->type);
-
-    CV_Assert( corr_cn == 1 || delta == 0 );
-
-    max_depth = MAX( max_depth, templ_depth );
-    max_depth = MAX( max_depth, depth );
-    max_depth = MAX( max_depth, corr_depth );
-    if( depth > CV_8U )
-        max_depth = CV_64F;
-
-    /*if( img->cols < templ->cols || img->rows < templ->rows )
-        CV_Error( CV_StsUnmatchedSizes,
-        "Such a combination of image and template/filter size is not supported" );*/
-
-    if( corr->rows > img->rows + templ->rows - 1 ||
-        corr->cols > img->cols + templ->cols - 1 )
-        CV_Error( CV_StsUnmatchedSizes,
-        "output image should not be greater than (W + w - 1)x(H + h - 1)" );
-
-    blocksize.width = cvRound(templ->cols*block_scale);
-    blocksize.width = MAX( blocksize.width, min_block_size - templ->cols + 1 );
-    blocksize.width = MIN( blocksize.width, corr->cols );
-    blocksize.height = cvRound(templ->rows*block_scale);
-    blocksize.height = MAX( blocksize.height, min_block_size - templ->rows + 1 );
-    blocksize.height = MIN( blocksize.height, corr->rows );
-
-    dftsize.width = cvGetOptimalDFTSize(blocksize.width + templ->cols - 1);
-    if( dftsize.width == 1 )
-        dftsize.width = 2;
-    dftsize.height = cvGetOptimalDFTSize(blocksize.height + templ->rows - 1);
+    dftsize.width = std::max(getOptimalDFTSize(blocksize.width + templ.cols - 1), 2);
+    dftsize.height = getOptimalDFTSize(blocksize.height + templ.rows - 1);
     if( dftsize.width <= 0 || dftsize.height <= 0 )
         CV_Error( CV_StsOutOfRange, "the input arrays are too big" );
 
     // recompute block size
-    blocksize.width = dftsize.width - templ->cols + 1;
-    blocksize.width = MIN( blocksize.width, corr->cols );
-    blocksize.height = dftsize.height - templ->rows + 1;
-    blocksize.height = MIN( blocksize.height, corr->rows );
+    blocksize.width = dftsize.width - templ.cols + 1;
+    blocksize.width = MIN( blocksize.width, corr.cols );
+    blocksize.height = dftsize.height - templ.rows + 1;
+    blocksize.height = MIN( blocksize.height, corr.rows );
 
-    dft_templ = cvCreateMat( dftsize.height*templ_cn, dftsize.width, max_depth );
+    Mat dftTempl( dftsize.height*tcn, dftsize.width, maxDepth );
+    Mat dftImg( dftsize, maxDepth );
 
-#ifdef USE_OPENMP
-    num_threads = cvGetNumThreads();
-#else
-    num_threads = 1;
-#endif
+    int i, k, bufSize = 0;
+    if( tcn > 1 && tdepth != maxDepth )
+        bufSize = templ.cols*templ.rows*CV_ELEM_SIZE(tdepth);
 
-    for( k = 0; k < num_threads; k++ )
-        dft_img[k] = cvCreateMat( dftsize.height, dftsize.width, max_depth );
+    if( cn > 1 && depth != maxDepth )
+        bufSize = std::max( bufSize, (blocksize.width + templ.cols - 1)*
+            (blocksize.height + templ.rows - 1)*CV_ELEM_SIZE(depth));
 
-    if( templ_cn > 1 && templ_depth != max_depth )
-        buf_size = templ->cols*templ->rows*CV_ELEM_SIZE(templ_depth);
+    if( (ccn > 1 || cn > 1) && cdepth != maxDepth )
+        bufSize = std::max( bufSize, blocksize.width*blocksize.height*CV_ELEM_SIZE(cdepth));
 
-    if( cn > 1 && depth != max_depth )
-        buf_size = MAX( buf_size, (blocksize.width + templ->cols - 1)*
-            (blocksize.height + templ->rows - 1)*CV_ELEM_SIZE(depth));
-
-    if( (corr_cn > 1 || cn > 1) && corr_depth != max_depth )
-        buf_size = MAX( buf_size, blocksize.width*blocksize.height*CV_ELEM_SIZE(corr_depth));
-
-    if( buf_size > 0 )
-    {
-        for( k = 0; k < num_threads; k++ )
-            buf[k].resize(buf_size);
-    }
-
-    // compute DFT of each template plane
-    for( k = 0; k < templ_cn; k++ )
-    {
-        CvMat dstub, *src, *dst, temp;
-        CvMat* planes[] = { 0, 0, 0, 0 };
-        int yofs = k*dftsize.height;
-
-        src = templ;
-        dst = cvGetSubRect( dft_templ, &dstub, cvRect(0,yofs,templ->cols,templ->rows));
+    buf.resize(bufSize);
     
-        if( templ_cn > 1 )
+    // compute DFT of each template plane
+    for( k = 0; k < tcn; k++ )
+    {
+        int yofs = k*dftsize.height;
+        Mat src = templ;
+        Mat dst(dftTempl, Rect(0, yofs, dftsize.width, dftsize.height));
+        Mat dst1(dftTempl, Rect(0, yofs, templ.cols, templ.rows));
+
+        if( tcn > 1 )
         {
-            planes[k] = templ_depth == max_depth ? dst :
-                cvInitMatHeader( &temp, templ->rows, templ->cols, templ_depth, &buf[0][0] );
-            cvSplit( templ, planes[0], planes[1], planes[2], planes[3] );
-            src = planes[k];
-            planes[k] = 0;
+            src = tdepth == maxDepth ? dst1 : Mat(templ.size(), tdepth, &buf[0]);
+            int pairs[] = {k, 0};
+            mixChannels(&templ, 1, &src, 1, pairs, 1);
         }
 
-        if( dst != src )
-            cvConvert( src, dst );
+        if( dst1.data != src.data )
+            src.convertTo(dst1, dst1.depth());
 
-        if( dft_templ->cols > templ->cols )
+        if( dst.cols > templ.cols )
         {
-            cvGetSubRect( dft_templ, dst, cvRect(templ->cols, yofs,
-                          dft_templ->cols - templ->cols, templ->rows) );
-            cvZero( dst );
+            Mat part(dst, Range(0, templ.rows), Range(templ.cols, dst.cols));
+            part = Scalar::all(0);
         }
-        cvGetSubRect( dft_templ, dst, cvRect(0,yofs,dftsize.width,dftsize.height) );
-        cvDFT( dst, dst, CV_DXT_FORWARD + CV_DXT_SCALE, templ->rows );
+        dft(dst, dst, 0, templ.rows);
     }
 
-    tile_count_x = (corr->cols + blocksize.width - 1)/blocksize.width;
-    tile_count_y = (corr->rows + blocksize.height - 1)/blocksize.height;
-    tile_count = tile_count_x*tile_count_y;
-
-#if defined _OPENMP && defined USE_OPENMP
-    #pragma omp parallel for num_threads(num_threads) schedule(dynamic)
-#endif
-    // calculate correlation by blocks
-    for( k = 0; k < tile_count; k++ )
+    int tileCountX = (corr.cols + blocksize.width - 1)/blocksize.width;
+    int tileCountY = (corr.rows + blocksize.height - 1)/blocksize.height;
+    int tileCount = tileCountX * tileCountY;
+    
+    Size wholeSize = img.size();
+    Point roiofs(0,0);
+    Mat img0 = img;
+    
+    if( !(borderType & BORDER_ISOLATED) )
     {
-#ifdef USE_OPENMP
-        int thread_idx = cvGetThreadNum();
-#else
-        int thread_idx = 0;
-#endif
-        int x = (k%tile_count_x)*blocksize.width;
-        int y = (k/tile_count_x)*blocksize.height;
-        int i, yofs;
-        CvMat sstub, dstub, *src, *dst, temp;
-        CvMat* planes[] = { 0, 0, 0, 0 };
-        CvMat* _dft_img = dft_img[thread_idx];
-        uchar* _buf = buf_size > 0 ? &buf[thread_idx][0] : 0;
-        CvSize csz = { blocksize.width, blocksize.height }, isz;
-        int x0 = x - anchor.x, y0 = y - anchor.y;
-        int x1 = MAX( 0, x0 ), y1 = MAX( 0, y0 ), x2, y2;
-        csz.width = MIN( csz.width, corr->cols - x );
-        csz.height = MIN( csz.height, corr->rows - y );
-        isz.width = csz.width + templ->cols - 1;
-        isz.height = csz.height + templ->rows - 1;
-        x2 = MIN( img->cols, x0 + isz.width );
-        y2 = MIN( img->rows, y0 + isz.height );
+        img.locateROI(wholeSize, roiofs);
+        img0.adjustROI(roiofs.y, wholeSize.height-img.rows-roiofs.y,
+                       roiofs.x, wholeSize.width-img.cols-roiofs.x);
+    }
+    
+    // calculate correlation by blocks
+    for( i = 0; i < tileCount; i++ )
+    {
+        int x = (i%tileCountX)*blocksize.width;
+        int y = (i/tileCountX)*blocksize.height;
         
-        for( i = 0; i < cn; i++ )
+        Size bsz(std::min(blocksize.width, corr.cols - x),
+                 std::min(blocksize.height, corr.rows - y));
+        Size dsz(bsz.width + templ.cols - 1, bsz.height + templ.rows - 1);
+        int x0 = x - anchor.x + roiofs.x, y0 = y - anchor.y + roiofs.y;
+        int x1 = std::max(0, x0), y1 = std::max(0, y0);
+        int x2 = std::min(img0.cols, x0 + dsz.width);
+        int y2 = std::min(img0.rows, y0 + dsz.height);
+        Mat src0(img0, Range(y1, y2), Range(x1, x2));
+        Mat dst(dftImg, Rect(0, 0, dsz.width, dsz.height));
+        Mat dst1(dftImg, Rect(x1-x0, y1-y0, x2-x1, y2-y1));
+        Mat cdst(corr, Rect(x, y, bsz.width, bsz.height));
+        
+        for( k = 0; k < cn; k++ )
         {
-            CvMat dstub1, *dst1;
-            yofs = i*dftsize.height;
-
-            src = cvGetSubRect( img, &sstub, cvRect(x1,y1,x2-x1,y2-y1) );
-            dst = cvGetSubRect( _dft_img, &dstub,
-                cvRect(0,0,isz.width,isz.height) );
-            dst1 = dst;
+            Mat src = src0;
             
-            if( x2 - x1 < isz.width || y2 - y1 < isz.height )
-                dst1 = cvGetSubRect( _dft_img, &dstub1,
-                    cvRect( x1 - x0, y1 - y0, x2 - x1, y2 - y1 ));
-
             if( cn > 1 )
             {
-                planes[i] = dst1;
-                if( depth != max_depth )
-                    planes[i] = cvInitMatHeader( &temp, y2 - y1, x2 - x1, depth, _buf );
-                cvSplit( src, planes[0], planes[1], planes[2], planes[3] );
-                src = planes[i];
-                planes[i] = 0;
+                src = depth == maxDepth ? dst1 : Mat(y2-y1, x2-x1, depth, &buf[0]);
+                int pairs[] = {k, 0};
+                mixChannels(&src0, 1, &src, 1, pairs, 1);
             }
 
-            if( dst1 != src )
-                cvConvert( src, dst1 );
+            if( dst1.data != src.data )
+                src.convertTo(dst1, dst1.depth());
 
-            if( dst != dst1 )
-                cvCopyMakeBorder( dst1, dst, cvPoint(x1 - x0, y1 - y0), borderType );
+            if( x2 - x1 < dsz.width || y2 - y1 < dsz.height )
+                copyMakeBorder(dst1, dst, y1-y0, dst.rows-dst1.rows-(y1-y0),
+                               x1-x0, dst.cols-dst1.cols-(x1-x0), borderType);
 
-            if( dftsize.width > isz.width )
+            if( dftsize.width > dsz.width )
             {
-                cvGetSubRect( _dft_img, dst, cvRect(isz.width, 0,
-                      dftsize.width - isz.width,dftsize.height) );
-                cvZero( dst );
+                Mat part(dftImg, Range(0, dsz.height), Range(dsz.width, dftsize.width));
+                part = Scalar::all(0);
             }
 
-            cvDFT( _dft_img, _dft_img, CV_DXT_FORWARD, isz.height );
-            cvGetSubRect( dft_templ, dst,
-                cvRect(0,(templ_cn>1?yofs:0),dftsize.width,dftsize.height) );
+            dft( dftImg, dftImg, 0, dsz.height );
+            Mat dftTempl1(dftTempl, Rect(0, tcn > 1 ? k*dftsize.height : 0,
+                                         dftsize.width, dftsize.height));
+            mulSpectrums(dftImg, dftTempl1, dftImg, 0, true);
+            dft( dftImg, dftImg, DFT_INVERSE + DFT_SCALE, bsz.height );
 
-            cvMulSpectrums( _dft_img, dst, _dft_img, CV_DXT_MUL_CONJ );
-            cvDFT( _dft_img, _dft_img, CV_DXT_INVERSE, csz.height );
+            src = dftImg(Rect(0, 0, bsz.width, bsz.height));
 
-            src = cvGetSubRect( _dft_img, &sstub, cvRect(0,0,csz.width,csz.height) );
-            dst = cvGetSubRect( corr, &dstub, cvRect(x,y,csz.width,csz.height) );
-
-            if( corr_cn > 1 )
+            if( ccn > 1 )
             {
-                planes[i] = src;
-                if( corr_depth != max_depth )
+                if( cdepth != maxDepth )
                 {
-                    planes[i] = cvInitMatHeader( &temp, csz.height, csz.width,
-                                                 corr_depth, _buf );
-                    cvConvertScale( src, planes[i], 1, delta );
+                    Mat plane(bsz, cdepth, &buf[0]);
+                    src.convertTo(plane, cdepth, 1, delta);
+                    src = plane;
                 }
-                cvMerge( planes[0], planes[1], planes[2], planes[3], dst );
-                planes[i] = 0;                    
+                int pairs[] = {0, k};
+                mixChannels(&src, 1, &cdst, 1, pairs, 1); 
             }
             else
             {
-                if( i == 0 )
-                    cvConvertScale( src, dst, 1, delta );
+                if( k == 0 )
+                    src.convertTo(cdst, cdepth, 1, delta);
                 else
                 {
-                    if( max_depth > corr_depth )
+                    if( maxDepth != cdepth )
                     {
-                        cvInitMatHeader( &temp, csz.height, csz.width,
-                                         corr_depth, _buf );
-                        cvConvert( src, &temp );
-                        src = &temp;
+                        Mat plane(bsz, cdepth, &buf[0]);
+                        src.convertTo(plane, cdepth);
+                        src = plane;
                     }
-                    cvAcc( src, dst );
+                    add(src, cdst, cdst);
                 }
             }
         }
     }
 }
 
-void
+/*void
 cv::crossCorr( const Mat& img, const Mat& templ, Mat& corr,
            Point anchor, double delta, int borderType )
 {
     CvMat _img = img, _templ = templ, _corr = corr;
     icvCrossCorr( &_img, &_templ, &_corr, anchor, delta, borderType );
-}
+}*/
 
 
 /*****************************************************************************************/
 
-CV_IMPL void
-cvMatchTemplate( const CvArr* _img, const CvArr* _templ, CvArr* _result, int method )
+void matchTemplate( const Mat& _img, const Mat& _templ, Mat& result, int method )
 {
-    cv::Ptr<CvMat> sum, sqsum;
+    CV_Assert( CV_TM_SQDIFF <= method && method <= CV_TM_CCOEFF_NORMED );
     
-    int coi1 = 0, coi2 = 0;
-    int depth, cn;
-    int i, j, k;
-    CvMat stub, *img = (CvMat*)_img;
-    CvMat tstub, *templ = (CvMat*)_templ;
-    CvMat rstub, *result = (CvMat*)_result;
-    CvScalar templ_mean = cvScalarAll(0);
-    double templ_norm = 0, templ_sum2 = 0;
-    
-    int idx = 0, idx2 = 0;
-    double *p0, *p1, *p2, *p3;
-    double *q0, *q1, *q2, *q3;
-    double inv_area;
-    int sum_step, sqsum_step;
-    int num_type = method == CV_TM_CCORR || method == CV_TM_CCORR_NORMED ? 0 :
-                   method == CV_TM_CCOEFF || method == CV_TM_CCOEFF_NORMED ? 1 : 2;
-    int is_normed = method == CV_TM_CCORR_NORMED ||
+    int numType = method == CV_TM_CCORR || method == CV_TM_CCORR_NORMED ? 0 :
+                  method == CV_TM_CCOEFF || method == CV_TM_CCOEFF_NORMED ? 1 : 2;
+    bool isNormed = method == CV_TM_CCORR_NORMED ||
                     method == CV_TM_SQDIFF_NORMED ||
                     method == CV_TM_CCOEFF_NORMED;
 
-    img = cvGetMat( img, &stub, &coi1 );
-    templ = cvGetMat( templ, &tstub, &coi2 );
-    result = cvGetMat( result, &rstub );
+    Mat img = _img, templ = _templ;
+    if( img.rows < templ.rows || img.cols < templ.cols )
+        std::swap(img, templ);
+    
+    CV_Assert( (img.depth() == CV_8U || img.depth() == CV_32F) &&
+               img.type() == templ.type() );
 
-    if( CV_MAT_DEPTH( img->type ) != CV_8U &&
-        CV_MAT_DEPTH( img->type ) != CV_32F )
-        CV_Error( CV_StsUnsupportedFormat,
-        "The function supports only 8u and 32f data types" );
-
-    if( !CV_ARE_TYPES_EQ( img, templ ))
-        CV_Error( CV_StsUnmatchedSizes, "image and template should have the same type" );
-
-    if( CV_MAT_TYPE( result->type ) != CV_32FC1 )
-        CV_Error( CV_StsUnsupportedFormat, "output image should have 32f type" );
-
-    if( img->rows < templ->rows || img->cols < templ->cols )
-    {
-        CvMat* t;
-        CV_SWAP( img, templ, t );
-    }
-
-    if( result->rows != img->rows - templ->rows + 1 ||
-        result->cols != img->cols - templ->cols + 1 )
-        CV_Error( CV_StsUnmatchedSizes, "output image should be (W - w + 1)x(H - h + 1)" );
-
-    if( method < CV_TM_SQDIFF || method > CV_TM_CCOEFF_NORMED )
-        CV_Error( CV_StsBadArg, "unknown comparison method" );
-
-    depth = CV_MAT_DEPTH(img->type);
-    cn = CV_MAT_CN(img->type);
-
-    icvCrossCorr( img, templ, result );
+    int cn = img.channels();
+    crossCorr( img, templ, result,
+               Size(img.cols - templ.cols + 1, img.rows - templ.rows + 1),
+               CV_32F, Point(0,0), 0, 0);
 
     if( method == CV_TM_CCORR )
         return;
 
-    inv_area = 1./((double)templ->rows * templ->cols);
+    double invArea = 1./((double)templ.rows * templ.cols);
 
-    sum = cvCreateMat( img->rows + 1, img->cols + 1, CV_MAKETYPE( CV_64F, cn ));
+    Mat sum, sqsum;
+    Scalar templMean, templSdv;
+    double *q0 = 0, *q1 = 0, *q2 = 0, *q3 = 0;
+    double templNorm = 0, templSum2 = 0;
+    
     if( method == CV_TM_CCOEFF )
     {
-        cvIntegral( img, sum, 0, 0 );
-        templ_mean = cvAvg( templ );
-        q0 = q1 = q2 = q3 = 0;
+        integral(img, sum, CV_64F);
+        templMean = mean(templ);
     }
     else
     {
-        CvScalar _templ_sdv = cvScalarAll(0);
-        sqsum = cvCreateMat( img->rows + 1, img->cols + 1, CV_MAKETYPE( CV_64F, cn ));
-        cvIntegral( img, sum, sqsum, 0 );
-        cvAvgSdv( templ, &templ_mean, &_templ_sdv );
+        integral(img, sum, sqsum, CV_64F);
+        meanStdDev( templ, templMean, templSdv );
 
-        templ_norm = CV_SQR(_templ_sdv.val[0]) + CV_SQR(_templ_sdv.val[1]) +
-                    CV_SQR(_templ_sdv.val[2]) + CV_SQR(_templ_sdv.val[3]);
+        templNorm = CV_SQR(templSdv[0]) + CV_SQR(templSdv[1]) +
+                    CV_SQR(templSdv[2]) + CV_SQR(templSdv[3]);
 
-        if( templ_norm < DBL_EPSILON && method == CV_TM_CCOEFF_NORMED )
+        if( templNorm < DBL_EPSILON && method == CV_TM_CCOEFF_NORMED )
         {
-            cvSet( result, cvScalarAll(1.) );
+            result = Scalar::all(1);
             return;
         }
         
-        templ_sum2 = templ_norm +
-                     CV_SQR(templ_mean.val[0]) + CV_SQR(templ_mean.val[1]) +
-                     CV_SQR(templ_mean.val[2]) + CV_SQR(templ_mean.val[3]);
+        templSum2 = templNorm +
+                     CV_SQR(templMean[0]) + CV_SQR(templMean[1]) +
+                     CV_SQR(templMean[2]) + CV_SQR(templMean[3]);
 
-        if( num_type != 1 )
+        if( numType != 1 )
         {
-            templ_mean = cvScalarAll(0);
-            templ_norm = templ_sum2;
+            templMean = Scalar::all(0);
+            templNorm = templSum2;
         }
         
-        templ_sum2 /= inv_area;
-        templ_norm = sqrt(templ_norm);
-        templ_norm /= sqrt(inv_area); // care of accuracy here
+        templSum2 /= invArea;
+        templNorm = sqrt(templNorm);
+        templNorm /= sqrt(invArea); // care of accuracy here
 
-        q0 = (double*)sqsum->data.ptr;
-        q1 = q0 + templ->cols*cn;
-        q2 = (double*)(sqsum->data.ptr + templ->rows*sqsum->step);
-        q3 = q2 + templ->cols*cn;
+        q0 = (double*)sqsum.data;
+        q1 = q0 + templ.cols*cn;
+        q2 = (double*)(sqsum.data + templ.rows*sqsum.step);
+        q3 = q2 + templ.cols*cn;
     }
 
-    p0 = (double*)sum->data.ptr;
-    p1 = p0 + templ->cols*cn;
-    p2 = (double*)(sum->data.ptr + templ->rows*sum->step);
-    p3 = p2 + templ->cols*cn;
+    double* p0 = (double*)sum.data;
+    double* p1 = p0 + templ.cols*cn;
+    double* p2 = (double*)(sum.data + templ.rows*sum.step);
+    double* p3 = p2 + templ.cols*cn;
 
-    sum_step = sum ? sum->step / sizeof(double) : 0;
-    sqsum_step = sqsum ? sqsum->step / sizeof(double) : 0;
+    int sumstep = sum.data ? sum.step / sizeof(double) : 0;
+    int sqstep = sqsum.data ? sqsum.step / sizeof(double) : 0;
 
-    for( i = 0; i < result->rows; i++ )
+    int i, j, k;
+    
+    for( i = 0; i < result.rows; i++ )
     {
-        float* rrow = (float*)(result->data.ptr + i*result->step);
-        idx = i * sum_step;
-        idx2 = i * sqsum_step;
+        float* rrow = (float*)(result.data + i*result.step);
+        int idx = i * sumstep;
+        int idx2 = i * sqstep;
 
-        for( j = 0; j < result->cols; j++, idx += cn, idx2 += cn )
+        for( j = 0; j < result.cols; j++, idx += cn, idx2 += cn )
         {
             double num = rrow[j], t;
-            double wnd_mean2 = 0, wnd_sum2 = 0;
+            double wndMean2 = 0, wndSum2 = 0;
             
-            if( num_type == 1 )
+            if( numType == 1 )
             {
                 for( k = 0; k < cn; k++ )
                 {
                     t = p0[idx+k] - p1[idx+k] - p2[idx+k] + p3[idx+k];
-                    wnd_mean2 += CV_SQR(t);
-                    num -= t*templ_mean.val[k];
+                    wndMean2 += CV_SQR(t);
+                    num -= t*templMean[k];
                 }
 
-                wnd_mean2 *= inv_area;
+                wndMean2 *= invArea;
             }
 
-            if( is_normed || num_type == 2 )
+            if( isNormed || numType == 2 )
             {
                 for( k = 0; k < cn; k++ )
                 {
                     t = q0[idx2+k] - q1[idx2+k] - q2[idx2+k] + q3[idx2+k];
-                    wnd_sum2 += t;
+                    wndSum2 += t;
                 }
 
-                if( num_type == 2 )
-                    num = wnd_sum2 - 2*num + templ_sum2;
+                if( numType == 2 )
+                    num = wndSum2 - 2*num + templSum2;
             }
 
-            if( is_normed )
+            if( isNormed )
             {
-                t = sqrt(MAX(wnd_sum2 - wnd_mean2,0))*templ_norm;
+                t = sqrt(MAX(wndSum2 - wndMean2,0))*templNorm;
                 if( fabs(num) < t )
                     num /= t;
                 else if( fabs(num) < t*1.125 )
@@ -477,12 +368,18 @@ cvMatchTemplate( const CvArr* _img, const CvArr* _templ, CvArr* _result, int met
     }
 }
 
-void cv::matchTemplate( const Mat& image, const Mat& templ, Mat& result, int method )
+}
+
+
+CV_IMPL void
+cvMatchTemplate( const CvArr* _img, const CvArr* _templ, CvArr* _result, int method )
 {
-    result.create( std::abs(image.rows - templ.rows) + 1,
-                   std::abs(image.cols - templ.cols) + 1, CV_32F );
-    CvMat _image = image, _templ = templ, _result = result;
-    cvMatchTemplate( &_image, &_templ, &_result, method );    
+    cv::Mat img = cv::cvarrToMat(_img), templ = cv::cvarrToMat(_templ),
+        result = cv::cvarrToMat(_result);
+    CV_Assert( result.size() == cv::Size(std::abs(img.cols - templ.cols) + 1,
+                                         std::abs(img.rows - templ.rows) + 1) &&
+              result.type() == CV_32F );
+    matchTemplate(img, templ, result, method);
 }
 
 /* End of file. */