Implementing OpenCV's probabilistic Hough line transform in Java-javaTutorial-php.cn

Use the Hough line transform to detect straight lines in a given image. There are two Hough line transforms available in OpenCV, namely standard Hough line transform and probabilistic Hough line transform.

You can apply theProbabilistic Hough Line Transformusing theHoughLinesP()method of the Imgproc class, which accepts the following parameters:

Two Mat objects representing the source image and the vector storing the line parameters (r, Φ).
Two double variables representing the resolution of parameters r (pixels) and Φ (radians).
An integer representing the minimum number of intersections required to "detect" a line.

Example

The following Java example uses OpenCV’s probabilistic Hough line transform to detect lines in an image:

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.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 HoughLineProbabilisticTransform 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.HoughLinesP(edges, lines, 1, Math.PI/180, 50, 50, 10); for (int i = 0; i < lines.rows(); i++) { double[] data = lines.get(i, 0); //Drawing lines on the image Point pt1 = new Point(data[0], data[1]); Point pt2 = new Point(data[2], data[3]); 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); } }

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Input image

Implementing OpenCVs probabilistic Hough line transform in Java

Output

After execution, the above code will produce the following output−

Implementing OpenCVs probabilistic Hough line transform in Java

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