houghTransform.cpp

#include <iostream>
#include <vector>

#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>

using namespace std;
using namespace cv;


int main() {

    Mat imgLines, imgCircles, detectImgLines, detectImgLinesP, detectImgCircles;
    imgLines = imread("/Users/kemik/OneDrive/Skrivebord/lines.jpg");
    imgCircles = imread("/Users/kemik/OneDrive/Skrivebord/circles.jpg");
  
    imgLines.copyTo(detectImgLines);
    imgLines.copyTo(detectImgLinesP);
    imgCircles.copyTo(detectImgCircles);


    // Line Detection Hough Transform
    // Edge detection
    Canny(imgLines, detectImgLines, 200, 255);
  
    // Standard Hough Line Transform
    vector<Vec2f> lines; // will hold the results of the detection
    HoughLines(detectImgLines, lines, 1, CV_PI, 150); // runs the actual detection
    // Draw the lines
    for (size_t i = 0; i < lines.size(); i++)
    {
        float rho = lines[i][0], theta = lines[i][1];
        Point pt1, pt2;
        double a = cos(theta), b = sin(theta);
        double x0 = a * rho, y0 = b * rho;
        pt1.x = cvRound(x0 + 1000 * (-b));
        pt1.y = cvRound(y0 + 1000 * (a));
        pt2.x = cvRound(x0 - 1000 * (-b));
        pt2.y = cvRound(y0 - 1000 * (a));
        line(detectImgLines, pt1, pt2, Scalar(0, 0, 255), 3, LINE_AA);
    }

    // Display
    imshow("Original Line Image", imgLines);
    imshow("Line Detection", detectImgLines);
    waitKey(0);


   
    // Probabilistic Line Transform
    Canny(imgLines, detectImgLinesP, 200, 255);

    vector<Vec4i> linesP; // will hold the results of the detection
    HoughLinesP(detectImgLinesP, linesP, 1, CV_PI / 180, 50, 50, 10); // runs the actual detection

    // Draw the lines
    for (size_t i = 0; i < linesP.size(); i++)
    {
        Vec4i l = linesP[i];
        line(detectImgLinesP, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(0, 0, 255), 1, LINE_AA);
    }
    
    imshow("Original Line Image", imgLines);
    imshow("Line Detection P", detectImgLinesP);
    waitKey(0);



    // Circle Detection Hough Transform

    Mat gray;
    cvtColor(imgCircles, gray, COLOR_RGB2GRAY);

    medianBlur(gray, gray, 5);

    vector<Vec3f> circles;
    HoughCircles(gray, circles, HOUGH_GRADIENT, 1,
        gray.rows / 16,  // change this value to detect circles with different distances to each other
        100, 30, 200, 500 // change the last two parameters
   // (min_radius & max_radius) to detect larger circles
    );

    for (size_t i = 0; i < circles.size(); i++)
    {
        Vec3i c = circles[i];
        Point center = Point(c[0], c[1]);
        // circle center
        circle(detectImgCircles, center, 1, Scalar(0, 100, 100), 3, LINE_AA);
        // circle outline
        int radius = c[2];

        circle(detectImgCircles, center, radius, Scalar(255, 0, 255), 3, LINE_AA);
    }

    imshow("Original Circle Image", imgCircles);
    imshow("Circle Detection", detectImgCircles);
    waitKey(0);


  return 0;
}