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OpenCV Hough Line Transform implementation using Java.
You can detect straight lines in a given image using the Hough line transform. There are two kinds of Hough line transforms available in OpenCV namely, Standard Hough line transform and, Probabilistic Hough Line Transform.
You can apply the Standard Hough line transform using the HoughLines() method of the Imgproc class. This method accepts −
Two Mat objects representing source image and the vector that stores the parameters (r, Φ) of the lines.
Two double variables representing the resolution of the parameters r (pixels) and Φ (radians).
An integer representing the minimum number of intersections to “detect” a line.
You can apply Probabilistic Hough line transform using the HoughLinesP() method of the Imgproc class (same parameters)
You can detect edges in a given image using the Canny() method of the Imgproc class. This method accepts −
Two Mat objects representing the source and destination images.
Two double variables to hold the threshold values.
To detect the edges of a given image using the canny edge detector −
Read the contents of the source image using the imread() method of the Imgcodecs class.
Convert it into a grayscale image using the cvtColor() method of the Imgproc class.
Blur the resultant (gray) image using the blur() method of the Imgproc class with kernel value 3.
Apply the canny edge detection algorithm on the blurred image using the canny() method of the Imgproc.
Create an empty matrix with all values as 0.
Add the detected edges to it using the copyTo() method of the Mat class.
Example
import java.awt.Image;
import java.awt.image.BufferedImage;
import java.io.IOException;
import javafx.application.Application;
import javafx.embed.swing.SwingFXUtils;
import javafx.scene.Group;
import javafx.scene.Scene;
import javafx.scene.image.ImageView;
import javafx.scene.image.WritableImage;
import javafx.stage.Stage;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
public class HoughLineTransform extends Application {
public void start(Stage stage) throws IOException {
//Loading the OpenCV core library
System.loadLibrary( Core.NATIVE_LIBRARY_NAME );
String file ="D:\Images\road4.jpg";
Mat src = Imgcodecs.imread(file);
//Converting the image to Gray
Mat gray = new Mat();
Imgproc.cvtColor(src, gray, Imgproc.COLOR_RGBA2GRAY);
//Detecting the edges
Mat edges = new Mat();
Imgproc.Canny(gray, edges, 60, 60*3, 3, false);
// Changing the color of the canny
Mat cannyColor = new Mat();
Imgproc.cvtColor(edges, cannyColor, Imgproc.COLOR_GRAY2BGR);
//Detecting the hough lines from (canny)
Mat lines = new Mat();
Imgproc.HoughLines(edges, lines, 1, Math.PI/180, 150);
for (int i = 0; i < lines.rows(); i++) {
double[] data = lines.get(i, 0);
double rho = data[0];
double theta = data[1];
double a = Math.cos(theta);
double b = Math.sin(theta);
double x0 = a*rho;
double y0 = b*rho;
//Drawing lines on the image
Point pt1 = new Point();
Point pt2 = new Point();
pt1.x = Math.round(x0 + 1000*(-b));
pt1.y = Math.round(y0 + 1000*(a));
pt2.x = Math.round(x0 - 1000*(-b));
pt2.y = Math.round(y0 - 1000 *(a));
Imgproc.line(cannyColor, pt1, pt2, new Scalar(0, 0, 255), 3);
}
//Converting matrix to JavaFX writable image
Image img = HighGui.toBufferedImage(cannyColor);
WritableImage writableImage= SwingFXUtils.toFXImage((BufferedImage) img, null);
//Setting the image view
ImageView imageView = new ImageView(writableImage);
imageView.setX(10);
imageView.setY(10);
imageView.setFitWidth(575);
imageView.setPreserveRatio(true);
//Setting the Scene object
Group root = new Group(imageView);
Scene scene = new Scene(root, 595, 400);
stage.setTitle("Hough Line Transform");
stage.setScene(scene);
stage.show();
}
public static void main(String args[]) {
launch(args);
}
}Input Image
Output
On executing, the above produces the following output −
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