Kantendetection und Liniendetection

Processing/processing.cpp

@@ -8,15 +8,49 @@ Processing::~Processing()
 {
 }
 
+static double angle( Point pt1, Point pt2, Point pt0 )
+{
+    double dx1 = pt1.x - pt0.x;
+    double dy1 = pt1.y - pt0.y;
+    double dx2 = pt2.x - pt0.x;
+    double dy2 = pt2.y - pt0.y;
+    return (dx1*dx2 + dy1*dy2)/sqrt((dx1*dx1 + dy1*dy1)*(dx2*dx2 + dy2*dy2) + 1e-10);
+}
+
 void Processing::processImage(Mat& inputPicture, int thresholdValue, int gaussKernelSize)
 {
     //Idea here is: Processing module consists of two methods:
     // One (this) to do all kinds of stuff to the picture (grayscale conversion, threshold, gauss etc etc)
     // And one (the other one) to segment the lines.
     // No return value here as the input is passed by reference -> directly modified.
+    vector<Vec4i> lines;
+    
+
     cvtColor(inputPicture, inputPicture, COLOR_BGR2GRAY);
     threshold(inputPicture, inputPicture, thresholdValue, 255, THRESH_BINARY);
     GaussianBlur(inputPicture, inputPicture, Size(gaussKernelSize, gaussKernelSize), 0);
+    
+    Canny(inputPicture, inputPicture, 50, 200, 3);
+
+    HoughLinesP(inputPicture, lines, 1, CV_PI/180, 150, 0, 0);  
+    //Draw lines  
+    for( size_t i = 0; i < lines.size(); i++ )
+    {
+        line( inputPicture, Point(lines[i][0], lines[i][1]),
+        Point( lines[i][2], lines[i][3]), Scalar(0,0,255), 3, 8 );
+    }
+
+    imshow("Result", inputPicture);
+    waitKey(0);
+    destroyWindow("Result");
+
+    for( size_t i = 0; i < lines.size(); i++ )
+    {
+        line( inputPicture, Point(lines[i][0], lines[i][1]),
+        Point( lines[i][2], lines[i][3]), Scalar(0,0,255), 3, 8 );
+        
+    }
+    
 }
 
 std::vector<LFRLine> Processing::calculateLineSegments(const Mat& inputPicture)

Processing/processing.h

@@ -1,8 +1,10 @@
 #include <iostream>
 #include <opencv2/opencv.hpp>
 #include <utils.h>
+#include <vector>
 
 using namespace cv;
+using namespace std;
 
 class Processing
 {