added DIST_LABEL_PIXEL labelType to distanceTransform, ticket #1641 (thanks to…

added DIST_LABEL_PIXEL labelType to distanceTransform, ticket #1641 (thanks to Mikhail Matrosov for the patch)

modules/imgproc/doc/miscellaneous_transformations.rst

@@ -412,11 +412,11 @@ Calculates the distance to the closest zero pixel for each pixel of the source i
 
 .. ocv:function:: void distanceTransform( InputArray src, OutputArray dst, int distanceType, int maskSize )
 
-.. ocv:function:: void distanceTransform( InputArray src, OutputArray dst, OutputArray labels, int distanceType, int maskSize )
+.. ocv:function:: void distanceTransform( InputArray src, OutputArray dst, OutputArray labels, int distanceType, int maskSize, int labelType=DIST_LABEL_CCOMP )
 
-.. ocv:pyfunction:: cv2.distanceTransform(src, distanceType, maskSize[, dst[, labels]]) -> dst, labels
+.. ocv:pyfunction:: cv2.distanceTransform(src, distanceType, maskSize[, dst[, labels[, labelType=cv2.DIST_LABEL_CCOMP]]]) -> dst, labels
 
-.. ocv:cfunction:: void cvDistTransform( const CvArr* src, CvArr* dst, int distanceType=CV_DIST_L2, int maskSize=3, const float* mask=NULL, CvArr* labels=NULL )
+.. ocv:cfunction:: void cvDistTransform( const CvArr* src, CvArr* dst, int distanceType=CV_DIST_L2, int maskSize=3, const float* mask=NULL, CvArr* labels=NULL, int labelType=CV_DIST_LABEL_CCOMP )
 
 .. ocv:pyoldfunction:: cv.DistTransform(src, dst, distanceType=CV_DIST_L2, maskSize=3, mask=None, labels=None)-> None
 
@@ -430,6 +430,8 @@ Calculates the distance to the closest zero pixel for each pixel of the source i
 
     :param labels: Optional output 2D array of labels (the discrete Voronoi diagram). It has the type  ``CV_32SC1``  and the same size as  ``src`` . See the details below.
     
+    :param labelType: Type of the label array to build. If ``labelType==DIST_LABEL_CCOMP`` then each connected component of zeros in ``src`` (as well as all the non-zero pixels closest to the connected component) will be assigned the same label. If ``labelType==DIST_LABEL_PIXEL`` then each zero pixel (and all the non-zero pixels closest to it) gets its own label.
+
 The functions ``distanceTransform`` calculate the approximate or precise
 distance from every binary image pixel to the nearest zero pixel.
 For zero image pixels, the distance will obviously be zero.
@@ -469,17 +471,13 @@ Note that both the precise and the approximate algorithms are linear on the numb
 
 The second variant of the function does not only compute the minimum distance for each pixel
 :math:`(x, y)` but also identifies the nearest connected
-component consisting of zero pixels. Index of the component is stored in
+component consisting of zero pixels (``labelType==DIST_LABEL_CCOMP``) or the nearest zero pixel (``labelType==DIST_LABEL_PIXEL``). Index of the component/pixel is stored in
 :math:`\texttt{labels}(x, y)` .
-The connected components of zero pixels are also found and marked by the function.
+When ``labelType==DIST_LABEL_CCOMP``, the function automatically finds connected components of zero pixels in the input image and marks them with distinct labels. When ``labelType==DIST_LABEL_CCOMP``, the function scans through the input image and marks all the zero pixels with distinct labels.
 
 In this mode, the complexity is still linear.
 That is, the function provides a very fast way to compute the Voronoi diagram for a binary image.
-Currently, the second variant can use only the approximate distance transform algorithm.
-
-
-
-
+Currently, the second variant can use only the approximate distance transform algorithm, i.e. ``maskSize=CV_DIST_MASK_PRECISE`` is not supported yet.
 
 floodFill
 -------------

modules/imgproc/include/opencv2/imgproc/imgproc.hpp

@@ -751,9 +751,16 @@ CV_EXPORTS_W void grabCut( InputArray img, InputOutputArray mask, Rect rect,
                            InputOutputArray bgdModel, InputOutputArray fgdModel,
                            int iterCount, int mode = GC_EVAL );
 
+enum
+{
+    DIST_LABEL_CCOMP = 0,
+    DIST_LABEL_PIXEL = 1
+};
+    
 //! builds the discrete Voronoi diagram
 CV_EXPORTS_AS(distanceTransformWithLabels) void distanceTransform( InputArray src, OutputArray dst,
-                                     OutputArray labels, int distanceType, int maskSize );
+                                     OutputArray labels, int distanceType, int maskSize,
+                                     int labelType=DIST_LABEL_CCOMP );
 
 //! computes the distance transform map
 CV_EXPORTS_W void distanceTransform( InputArray src, OutputArray dst,

modules/imgproc/include/opencv2/imgproc/imgproc_c.h

@@ -620,7 +620,8 @@ CVAPI(void)  cvDistTransform( const CvArr* src, CvArr* dst,
                               int distance_type CV_DEFAULT(CV_DIST_L2),
                               int mask_size CV_DEFAULT(3),
                               const float* mask CV_DEFAULT(NULL),
-                              CvArr* labels CV_DEFAULT(NULL));
+                              CvArr* labels CV_DEFAULT(NULL),
+                              int labelType CV_DEFAULT(CV_DIST_LABEL_CCOMP));
 
 
 /* Applies fixed-level threshold to grayscale image.

modules/imgproc/include/opencv2/imgproc/types_c.h

@@ -470,6 +470,13 @@ enum
     CV_DIST_MASK_PRECISE =0
 };
 
+/* Content of output label array: connected components or pixels */
+enum
+{
+  CV_DIST_LABEL_CCOMP = 0,
+  CV_DIST_LABEL_PIXEL = 1
+};
+
 /* Distance types for Distance Transform and M-estimators */
 enum
 {

modules/imgproc/src/distransform.cpp

@@ -706,19 +706,12 @@ CV_IMPL void
 cvDistTransform( const void* srcarr, void* dstarr,
                  int distType, int maskSize,
                  const float *mask,
-                 void* labelsarr )
+                 void* labelsarr, int labelType )
 {
-    cv::Ptr<CvMat> temp;
-    cv::Ptr<CvMat> src_copy;
-    cv::Ptr<CvMemStorage> st;
-    
     float _mask[5] = {0};
     CvMat srcstub, *src = (CvMat*)srcarr;
     CvMat dststub, *dst = (CvMat*)dstarr;
     CvMat lstub, *labels = (CvMat*)labelsarr;
-    CvSize size;
-    //CvIPPDistTransFunc ipp_func = 0;
-    //CvIPPDistTransFunc2 ipp_inp_func = 0;
 
     src = cvGetMat( src, &srcstub );
     dst = cvGetMat( dst, &dststub );
@@ -773,46 +766,16 @@ cvDistTransform( const void* srcarr, void* dstarr,
         memcpy( _mask, mask, (maskSize/2 + 1)*sizeof(float));
     }
 
-    /*if( !labels )
-    {
-        if( CV_MAT_TYPE(dst->type) == CV_32FC1 )
-            ipp_func = (CvIPPDistTransFunc)(maskSize == CV_DIST_MASK_3 ?
-                icvDistanceTransform_3x3_8u32f_C1R_p : icvDistanceTransform_5x5_8u32f_C1R_p);
-        else if( src->data.ptr != dst->data.ptr )
-            ipp_func = (CvIPPDistTransFunc)icvDistanceTransform_3x3_8u_C1R_p;
-        else
-            ipp_inp_func = icvDistanceTransform_3x3_8u_C1IR_p;
-    }*/
-
-    size = cvGetMatSize(src);
+    CvSize size = cvGetMatSize(src);
 
-    /*if( (ipp_func || ipp_inp_func) && src->cols >= 4 && src->rows >= 2 )
-    {
-        int _imask[3];
-        _imask[0] = cvRound(_mask[0]);
-        _imask[1] = cvRound(_mask[1]);
-        _imask[2] = cvRound(_mask[2]);
-
-        if( ipp_func )
-        {
-            IPPI_CALL( ipp_func( src->data.ptr, src->step,
-                    dst->data.fl, dst->step, size,
-                    CV_MAT_TYPE(dst->type) == CV_8UC1 ?
-                    (void*)_imask : (void*)_mask ));
-        }
-        else
-        {
-            IPPI_CALL( ipp_inp_func( src->data.ptr, src->step, size, _imask ));
-        }
-    }
-    else*/ if( CV_MAT_TYPE(dst->type) == CV_8UC1 )
+    if( CV_MAT_TYPE(dst->type) == CV_8UC1 )
     {
         icvDistanceATS_L1_8u( src, dst );
     }
     else
     {
         int border = maskSize == CV_DIST_MASK_3 ? 1 : 2;
-        temp = cvCreateMat( size.height + border*2, size.width + border*2, CV_32SC1 );
+        cv::Ptr<CvMat> temp = cvCreateMat( size.height + border*2, size.width + border*2, CV_32SC1 );
 
         if( !labels )
         {
@@ -825,25 +788,37 @@ cvDistTransform( const void* srcarr, void* dstarr,
         }
         else
         {
-            CvSeq *contours = 0;
-            int label;
+            cvZero( labels );
             
-            st = cvCreateMemStorage();
-            src_copy = cvCreateMat( size.height+border*2, size.width+border*2, src->type );
+            if( labelType == CV_DIST_LABEL_CCOMP )
+            {
+                CvSeq *contours = 0;
+                cv::Ptr<CvMemStorage> st = cvCreateMemStorage();
+                cv::Ptr<CvMat> src_copy = cvCreateMat( size.height+border*2, size.width+border*2, src->type );
                 cvCopyMakeBorder(src, src_copy, cvPoint(border, border), IPL_BORDER_CONSTANT, cvScalarAll(255));
                 cvCmpS( src_copy, 0, src_copy, CV_CMP_EQ );
                 cvFindContours( src_copy, st, &contours, sizeof(CvContour),
                                CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE, cvPoint(-border, -border));
-            cvZero( labels );
-            for( label = 1; contours != 0; contours = contours->h_next, label++ )
+                
+                for( int label = 1; contours != 0; contours = contours->h_next, label++ )
                 {
                     CvScalar area_color = cvScalarAll(label);
                     cvDrawContours( labels, contours, area_color, area_color, -255, -1, 8 );
                 }
+            }
+            else
+            {
+                int k = 1;
+                for( int i = 0; i < src->rows; i++ )
+                {
+                    const uchar* srcptr = src->data.ptr + src->step*i;
+                    int* labelptr = (int*)(labels->data.ptr + labels->step*i);
                     
-            //cvCopy( src, src_copy );
-            //CvPoint top_left = {0,0}, bottom_right = {size.width-1,size.height-1};
-            //cvRectangle( src_copy, top_left, bottom_right, cvScalarAll(255), 1, 8 );
+                    for( int j = 0; j < src->cols; j++ )
+                        if( srcptr[j] == 0 )
+                            labelptr[j] = k++;
+                }
+            }
 
             icvDistanceTransformEx_5x5_C1R( src->data.ptr, src->step, temp->data.i, temp->step,
                         dst->data.fl, dst->step, labels->data.i, labels->step, size, _mask );
@@ -852,13 +827,13 @@ cvDistTransform( const void* srcarr, void* dstarr,
 }
 
 void cv::distanceTransform( InputArray _src, OutputArray _dst, OutputArray _labels,
-                            int distanceType, int maskSize )
+                            int distanceType, int maskSize, int labelType )
 {
     Mat src = _src.getMat();
     _dst.create(src.size(), CV_32F);
     _labels.create(src.size(), CV_32S);
     CvMat c_src = src, c_dst = _dst.getMat(), c_labels = _labels.getMat();
-    cvDistTransform(&c_src, &c_dst, distanceType, maskSize, 0, &c_labels);
+    cvDistTransform(&c_src, &c_dst, distanceType, maskSize, 0, &c_labels, labelType);
 }
 
 void cv::distanceTransform( InputArray _src, OutputArray _dst,
@@ -868,7 +843,7 @@ void cv::distanceTransform( InputArray _src, OutputArray _dst,
     _dst.create(src.size(), CV_32F);
     Mat dst = _dst.getMat();
     CvMat c_src = src, c_dst = _dst.getMat();
-    cvDistTransform(&c_src, &c_dst, distanceType, maskSize, 0, 0);
+    cvDistTransform(&c_src, &c_dst, distanceType, maskSize, 0, 0, -1);
 }
 
 /* End of file. */

samples/cpp/distrans.cpp

@@ -6,7 +6,7 @@
 using namespace cv;
 
 int maskSize0 = CV_DIST_MASK_5;
-bool buildVoronoi = false;
+int voronoiType = -1;
 int edgeThresh = 100;
 int distType0 = CV_DIST_L1;
 
@@ -29,17 +29,17 @@ void onTrackbar( int, void* )
         Scalar(255,0,255)
     };
 
-    int maskSize = buildVoronoi ? CV_DIST_MASK_5 : maskSize0;
-    int distType = buildVoronoi ? CV_DIST_L2 : distType0;
+    int maskSize = voronoiType >= 0 ? CV_DIST_MASK_5 : maskSize0;
+    int distType = voronoiType >= 0 ? CV_DIST_L2 : distType0;
 
     Mat edge = gray >= edgeThresh, dist, labels, dist8u;
 
-    if( !buildVoronoi )
+    if( voronoiType < 0 )
         distanceTransform( edge, dist, distType, maskSize );
     else
-        distanceTransform( edge, dist, labels, distType, maskSize );
+        distanceTransform( edge, dist, labels, distType, maskSize, voronoiType );
 
-    if( !buildVoronoi )
+    if( voronoiType < 0 )
     {
         // begin "painting" the distance transform result
         dist *= 5000;
@@ -70,9 +70,10 @@ void onTrackbar( int, void* )
             for( int j = 0; j < labels.cols; j++ )
             {
                 int idx = ll[j] == 0 || dd[j] == 0 ? 0 : (ll[j]-1)%8 + 1;
-                int b = cvRound(colors[idx][0]);
-                int g = cvRound(colors[idx][1]);
-                int r = cvRound(colors[idx][2]);
+                float scale = 1.f/(1 + dd[j]*dd[j]*0.0004f);
+                int b = cvRound(colors[idx][0]*scale);
+                int g = cvRound(colors[idx][1]*scale);
+                int r = cvRound(colors[idx][2]*scale);
                 d[j*3] = (uchar)b;
                 d[j*3+1] = (uchar)g;
                 d[j*3+2] = (uchar)r;
@@ -96,7 +97,8 @@ void help()
 			"\t3 - use 3x3 mask\n"
 			"\t5 - use 5x5 mask\n"
 			"\t0 - use precise distance transform\n"
-			"\tv - switch Voronoi diagram mode on/off\n"
+			"\tv - switch to Voronoi diagram mode\n"
+            "\tp - switch to pixel-based Voronoi diagram mode\n"
 			"\tSPACE - loop through all the modes\n\n");
 }
 
@@ -126,30 +128,38 @@ int main( int argc, const char** argv )
         // Call to update the view
         onTrackbar(0, 0);
 
-        int c = cvWaitKey(0);
+        int c = cvWaitKey(0) & 255;
 
-        if( (char)c == 27 )
+        if( c == 27 )
             break;
 
-        if( (char)c == 'c' || (char)c == 'C' )
+        if( c == 'c' || c == 'C' || c == '1' || c == '2' ||
+            c == '3' || c == '5' || c == '0' )
+            voronoiType = -1;
+        
+        if( c == 'c' || c == 'C' )
             distType0 = CV_DIST_C;
-        else if( (char)c == '1' )
+        else if( c == '1' )
             distType0 = CV_DIST_L1;
-        else if( (char)c == '2' )
+        else if( c == '2' )
             distType0 = CV_DIST_L2;
-        else if( (char)c == '3' )
+        else if( c == '3' )
             maskSize0 = CV_DIST_MASK_3;
-        else if( (char)c == '5' )
+        else if( c == '5' )
             maskSize0 = CV_DIST_MASK_5;
-        else if( (char)c == '0' )
+        else if( c == '0' )
             maskSize0 = CV_DIST_MASK_PRECISE;
-        else if( (char)c == 'v' )
-            buildVoronoi = !buildVoronoi;
-        else if( (char)c == ' ' )
+        else if( c == 'v' )
+            voronoiType = 0;
+        else if( c == 'p' )
+            voronoiType = 1;
+        else if( c == ' ' )
         {
-            if( buildVoronoi )
+            if( voronoiType == 0 )
+                voronoiType = 1;
+            else if( voronoiType == 1 )
             {
-                buildVoronoi = false;
+                voronoiType = -1;
                 maskSize0 = CV_DIST_MASK_3;
                 distType0 = CV_DIST_C;
             }
@@ -162,7 +172,7 @@ int main( int argc, const char** argv )
             else if( maskSize0 == CV_DIST_MASK_5 )
                 maskSize0 = CV_DIST_MASK_PRECISE;
             else if( maskSize0 == CV_DIST_MASK_PRECISE )
-                buildVoronoi = true;
+                voronoiType = 0;
         }
     }