change meanCol from bgr to cielab color space

Author: Masterqsx

modules/saliency/include/opencv2/saliency/saliencySpecializedClasses.hpp

@@ -218,14 +218,16 @@ class CV_EXPORTS_W BackgroundContrast : public StaticSaliency
         return computeSaliencyImpl( image, saliencyMap );
     }
     Mat saliencyMapGenerator( const Mat );
-    void saliencyMapVisualize( InputArray _saliencyMap );
+    Mat saliencyMapVisualize( InputArray _saliencyMap, int = 0 );
 protected:
     bool computeSaliencyImpl( InputArray image, OutputArray saliencyMap );
     void superpixelSplit( const Mat, Mat&, Mat& );
     std::vector<unsigned> getBndPatchIds( const Mat, int = 8);
     void getColorPosDis( const Mat, const Mat, Mat&, Mat&, int );
     void boundaryConnectivity( const Mat, const Mat, Mat&, std::vector<unsigned>, double = 3.0, double = 7.0 );
     void getWeightedContrast( const Mat, const Mat, const Mat, Mat& );
+    void dist2WeightMatrix( Mat&, Mat&, double );
+    void rgb2lab( Mat&, Mat& );
 };
 
 

modules/saliency/src/BackgroundContrast.cpp

@@ -48,7 +48,8 @@ Mat BackgroundContrast::saliencyMapGenerator( const Mat img )
     {
     	for (unsigned j = 0; j < bdIds.size(); j++)
     	{
-    		adjcMatrix.at<uchar>(i, j) = 1;
+    		adjcMatrix.at<uchar>(bdIds[i], bdIds[j]) = 1;
+    		adjcMatrix.at<uchar>(bdIds[j], bdIds[i]) = 1;
     	}
     }
     getColorPosDis(img, idxImg, colDistM, posDistM, adjcMatrix.size[0]);
@@ -63,6 +64,7 @@ Mat BackgroundContrast::saliencyMapGenerator( const Mat img )
     	}
     }
     return saliency;
+    return img;
 }
 
 bool BackgroundContrast::computeSaliencyImpl( InputArray image, OutputArray saliencyMap )
@@ -73,7 +75,7 @@ bool BackgroundContrast::computeSaliencyImpl( InputArray image, OutputArray sali
 void BackgroundContrast::superpixelSplit( const Mat img, Mat& idxImg, Mat& adjcMatrix)
 {
     Ptr<SuperpixelSEEDS> seeds;
-    seeds = createSuperpixelSEEDS( img.size().width, img.size().height, img.channels(), min(img.size().width  * img.size().height / 600, 300), 4, 2, 5, false);
+    seeds = createSuperpixelSEEDS( img.size().width, img.size().height, img.channels(), min(img.size().width  * img.size().height / 600, 3000), 4, 2, 5, false);
     seeds->iterate( img, 4 );
     Mat mask;
     adjcMatrix = Mat::eye( seeds->getNumberOfSuperpixels(), seeds->getNumberOfSuperpixels(), CV_8U );
@@ -155,7 +157,7 @@ void BackgroundContrast::getColorPosDis( const Mat img, const Mat idxImg, Mat& c
     }
     meanPos.col(0) /= img.size[0];
     meanPos.col(1) /= img.size[1];
-
+    rgb2lab(meanCol, meanCol);
     for ( int i = 0; i < meanCol.size[1]; i++)
     {
     	Mat temp = ( repeat(meanCol.col(i), 1, nOfSP) - repeat(meanCol.col(i).t(), nOfSP, 1) );
@@ -188,7 +190,7 @@ void BackgroundContrast::boundaryConnectivity(const Mat adjcMatrix, const Mat co
 	    	}
 	    	else
 	    	{
-	    	    geoDistMatrix.at<double>(i, j) = colDistM.at<double>(i, j);
+	    	    geoDistMatrix.at<double>(i, j) = max(0.0, colDistM.at<double>(i, j) - clipVal);
 	    	}
 	    }
 	}
@@ -203,9 +205,7 @@ void BackgroundContrast::boundaryConnectivity(const Mat adjcMatrix, const Mat co
 	    	}
 	    }
 	}
-	pow(geoDistMatrix, 2, geoDistMatrix);
-	geoDistMatrix /= (-1 * 2 * geoSigma * geoSigma);
-	exp(geoDistMatrix, geoDistMatrix);
+	dist2WeightMatrix(geoDistMatrix, geoDistMatrix, geoSigma);
 	bdProb = Mat(adjcMatrix.size[0], 1, CV_64F, Scalar::all(0.0));
 	for ( int i = 0; i < adjcMatrix.size[0]; i++ )
 	{
@@ -215,33 +215,74 @@ void BackgroundContrast::boundaryConnectivity(const Mat adjcMatrix, const Mat co
 	    }
 	    bdProb.at<double>(i, 0) /= sqrt(sum(geoDistMatrix.row(i)).val[0]);
 	}
-
-	pow(bdProb, 2, bdProb);
-	bdProb /= (-1 * 2);
-	exp(bdProb, bdProb);
+	dist2WeightMatrix(bdProb, bdProb, 1);
 	bdProb = 1 - bdProb;
 }
 
 void BackgroundContrast::getWeightedContrast( const Mat colDistM, const Mat posDistM, const Mat bgProb, Mat& wCtr )
 {
 	wCtr = posDistM.clone();
-	pow(wCtr, 2, wCtr);
-	wCtr /= (-1 * 2 * 0.16);
-	exp(wCtr, wCtr);
+	dist2WeightMatrix(wCtr,wCtr, 0.4);
 	multiply(colDistM, wCtr, wCtr);
 	wCtr *= bgProb;
 }
 
+void BackgroundContrast::dist2WeightMatrix( Mat& input, Mat& output, double sigma )
+{
+	Mat temp = input.clone();
+	output = input.clone();
+	for ( int i = 0; i < output.size[0]; i++ )
+	{
+		for ( int j = 0; j < output.size[1]; j++ )
+		{
+			//if (temp.at<double>(i, j) > 3 * sigma) output.at<double>(i, j) = 0;
+			//else
+			//{
+				output.at<double>(i, j) = exp(-1 * temp.at<double>(i, j) * temp.at<double>(i, j) / 2 / sigma / sigma);
+			//}
+		}
+	}
+}
+
+void BackgroundContrast::rgb2lab( Mat& inputMeanCol, Mat& outputMeanCol )
+{
+	Mat temp = Mat(inputMeanCol.size[0], 1, CV_32FC3, Scalar::all(0));
+	for ( int i = 0; i < inputMeanCol.size[0]; i++ )
+	{
+		temp.at<Vec3f>(i, 0)[0] = inputMeanCol.at<double>(i, 0) / 255;
+		temp.at<Vec3f>(i, 0)[1] = inputMeanCol.at<double>(i, 1) / 255;
+		temp.at<Vec3f>(i, 0)[2] = inputMeanCol.at<double>(i, 2) / 255;
+	}
+	cvtColor(temp, temp, COLOR_BGR2Lab);
+	outputMeanCol = inputMeanCol.clone();
+	for ( int i = 0; i < outputMeanCol.size[0]; i++ )
+	{
+		outputMeanCol.at<double>(i, 0) = temp.at<Vec3f>(i, 0)[0];
+		outputMeanCol.at<double>(i, 1) = temp.at<Vec3f>(i, 0)[1];
+		outputMeanCol.at<double>(i, 2) = temp.at<Vec3f>(i, 0)[2];
+	}
+}
 
-void BackgroundContrast::saliencyMapVisualize( InputArray _saliencyMap )
+Mat BackgroundContrast::saliencyMapVisualize( InputArray _saliencyMap, int option )
 {
     Mat saliency = _saliencyMap.getMat().clone();
+
     double mi = 0, ma = 0;
     minMaxLoc( saliency, &mi, &ma );
     saliency -= mi;
-    saliency /= ( ma - mi );
+    saliency /= ( ma - mi + 0.000001 );
+
+    if (option != 0 )
+    {
+    	saliency *= 255;
+    	saliency.convertTo(saliency, CV_8U);
+    	if (option == 1) threshold(saliency, saliency, 0, 255, THRESH_BINARY | THRESH_OTSU);
+    	else if (option == 2) threshold(saliency, saliency, 0, 255, THRESH_TOZERO | THRESH_OTSU);
+    	//threshold(saliency, saliency, 0, 255, THRESH_TOZERO | THRESH_OTSU);
+    }
     imshow( "saliencyVisual", saliency );
     waitKey( 0 );
+    return saliency;
 }
 
 }