Merge pull request #1330 from Jaykob:parallelize_structured_edge_detection

* Replace OpenMP parallelization with OpenCV's general parallel_for_ to cover other backends than OpenMP.

* Fixed shadowing of range variable in C++11 mode.

modules/ximgproc/src/structured_edge_detection.cpp

@@ -729,11 +729,14 @@ protected:
                 offsetY[n] = x2*features.cols*nchannels + y2*nchannels + z;
             }
             // lookup tables for mapping linear index to offset pairs
-        #ifdef _OPENMP
-        #pragma omp parallel for
+
+        #ifdef CV_CXX11
+        parallel_for_(cv::Range(0, height), [&](const cv::Range& range)
+        #else
+        const cv::Range range(0, height);
         #endif
-        for (int i = 0; i < height; ++i)
         {
+            for(int i = range.start; i < range.end; ++i) {
                 float *regFeaturesPtr = regFeatures.ptr<float>(i*stride/shrink);
                 float  *ssFeaturesPtr = ssFeatures.ptr<float>(i*stride/shrink);
 
@@ -775,16 +778,21 @@ protected:
                     indexPtr[j*nTreesEval + k] = currentNode;
                 }
             }
+        }
+        #ifdef CV_CXX11
+        );
+        #endif
 
         NChannelsMat dstM(dst.size(),
             CV_MAKETYPE(DataType<float>::type, outNum));
         dstM.setTo(0);
 
         float step = 2.0f * CV_SQR(stride) / CV_SQR(ipSize) / nTreesEval;
-        #ifdef _OPENMP
-        #pragma omp parallel for
+        #ifdef CV_CXX11
+        parallel_for_(cv::Range(0, height), [&](const cv::Range& range)
         #endif
-        for (int i = 0; i < height; ++i)
+        {
+            for(int i = range.start; i < range.end; ++i)
             {
                 int *pIndex = indexes.ptr<int>(i);
                 float *pDst = dstM.ptr<float>(i*stride);
@@ -805,6 +813,10 @@ protected:
                         pDst[offset + offsetE[__rf.edgeBins[p]]] += step;
                 }
             }
+        }
+        #ifdef CV_CXX11
+        );
+        #endif
 
         cv::reduce( dstM.reshape(1, int( dstM.total() ) ), dstM, 2, CV_REDUCE_SUM);
         imsmooth( dstM.reshape(1, dst.rows), 1 ).copyTo(dst);