Zad_11_

src/core/transformations/blur_gaussian.cpp

@@ -41,9 +41,8 @@ math::matrix<float> BlurGaussian::getMask(int size, Mode)
 }
 
 float BlurGaussian::getGauss(int x, int y, float sigma)
-{    
+{
 
     float gauss= exp(-(x*x+y*y)/(2*sigma*sigma))/(2*M_PI*sigma*sigma);
     return gauss;
 }
-

src/core/transformations/conversion_grayscale.cpp

@@ -65,4 +65,3 @@ PNM* ConversionGrayscale::transform()
     }
 
     return newImage;
-}

src/core/transformations/convolution.cpp

@@ -137,7 +137,7 @@ const math::matrix<float> Convolution::join(math::matrix<float> A, math::matrix<
 
     for (int x=0; x<size; x++)
             for (int y=0; y<size; y++)
-           {     
+           {
                 C[x][y]=A[x][y]*B[x][y];
            }
 
@@ -181,4 +181,3 @@ const math::matrix<float> Convolution::reflection(const math::matrix<float> A)
         }
 
     return C;
-}

src/core/transformations/edge_laplacian.cpp

@@ -10,9 +10,12 @@ EdgeLaplacian::EdgeLaplacian(PNM* img, ImageViewer* iv) :
 {
 }
 
-math::matrix<float> EdgeLaplacian::getMask(int, Mode)
+math::matrix<float> EdgeLaplacian::getMask(int size , Mode)
 {
-    int size = getParameter("size").toInt();
+
+    if( getParameter("size").toInt() > size )
+         size =getParameter("size").toInt();
+
     math::matrix<float> mask(size, size);
     int r=size/2;
 

src/core/transformations/edge_laplacian_of_gauss.cpp

@@ -12,11 +12,14 @@ EdgeLaplaceOfGauss::EdgeLaplaceOfGauss(PNM* img, ImageViewer* iv) :
 {
 }
 
-math::matrix<float> EdgeLaplaceOfGauss::getMask(int, Mode)
+math::matrix<float> EdgeLaplaceOfGauss::getMask(int size, Mode)
 {
-    size = getParameter("size").toInt();
+    if( getParameter("size").toInt() > size )
+         size =getParameter("size").toInt();
+
     double sigma = getParameter("sigma").toDouble();
 
+
     math::matrix<float> mask(size, size);
     int r=size/2;
 

src/core/transformations/edge_sobel.cpp

@@ -51,7 +51,7 @@ math::matrix<float>* EdgeSobel::rawHorizontalDetection()
         for (int y = 0; y < height; y++)
         {
             math::matrix<float> temp = getWindow(x, y, 3, LChannel, NullEdge);
-            x_gradient[x][y]  = Convolution::sum(Convolution::join(g_x, temp));
+            (*x_gradient)(x, y)  = Convolution::sum(Convolution::join(g_x, temp));
 
         }
     }
@@ -71,7 +71,7 @@ math::matrix<float>* EdgeSobel::rawVerticalDetection()
                 for (int y = 0; y < height; y++)
                 {
                     math::matrix<float> temp = getWindow(x, y, 3, LChannel, NullEdge);
-                    y_gradient[x][y] = Convolution::sum(Convolution::join(g_x, temp));
+                  (*y_gradient)(x, y) = Convolution::sum(Convolution::join(g_x, temp));
                 }
             }
 

src/core/transformations/hough.cpp

@@ -17,7 +17,50 @@ PNM* Hough::transform()
 {   
     int thetaDensity = getParameter("theta_density").toInt();
 
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
+     int width = image->width();
+     int height = image->height();
+     PNM* tempImage = new PNM(width, height, QImage::Format_Indexed8);
+     tempImage = ConversionGrayscale(image).transform();
 
-    return 0;
+     if (!getParameter("skip_edge_detection").toBool()) {
+         tempImage = EdgeLaplacian(tempImage).transform();
+     }
+
+     int pmax =int(sqrt(height*height + width*width));
+     int thetaSize= 180 * thetaDensity;
+     int lenght =  pmax * 2 + 1;
+     double theta, p;
+     int max = 0;
+
+     math::matrix<int> hough(thetaSize,lenght);
+
+     for (int i = 0; i < thetaSize; i++) {
+         for (int j = 0 ; j < lenght ; j++) {
+             hough[i][j] = 0;
+         }
+     }
+
+     for (int i = 0; i < width; i++) {
+         for (int j = 0; j < height; j++) {
+             if (qGray(tempImage->pixel(i, j)) > 0) {
+                 for (int k = 0; k < thetaSize; k++) {
+                     theta = (k * 3.14) / (180 * thetaDensity);
+                     p = i*cos(theta) + j*sin(theta);
+                     hough[k][p+pmax]++;
+                     if (hough[k][p+pmax] > max) {
+                         max = hough[k][p+pmax];
+                     }
+                 }
+             }
+         }
+     }
+
+     PNM* newImage = new PNM(thetaSize,lenght, QImage::Format_Grayscale8);
+     for (int i = 0; i < thetaSize; i++) {
+         for (int j = 0; j < lenght; j++) {
+             int value = int(((hough[i][j] * 255)/ max));
+             newImage->setPixel(i, j, QColor(value,value,value).rgb());
+         }
+     }
+     return newImage;
 }