java+对图像进行直线检测_Opencv Hough算法实现图片中直线检测

使用OpenCV中的HoughLines函数可以实现直线检测。以下是Java代码示例：

import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfFloat;
import org.opencv.core.MatOfPoint;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import java.util.ArrayList;
import java.util.List;

public class HoughLinesExample {
    public static void main(String[] args) {
        // Load the image
        Mat src = Imgcodecs.imread("input.jpg");

        // Convert the image to grayscale
        Mat gray = new Mat();
        Imgproc.cvtColor(src, gray, Imgproc.COLOR_BGR2GRAY);

        // Perform edge detection using Canny
        Mat edges = new Mat();
        Imgproc.Canny(gray, edges, 50, 150, 3, false);

        // Perform HoughLines transformation
        Mat lines = new Mat();
        Imgproc.HoughLines(edges, lines, 1, Math.PI / 180, 150);

        // Draw the detected lines on the original image
        List<MatOfPoint> contours = new ArrayList<>();
        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;
            Point pt1 = new Point(x0 + 1000 * (-b), y0 + 1000 * (a));
            Point pt2 = new Point(x0 - 1000 * (-b), y0 - 1000 * (a));
            Imgproc.line(src, pt1, pt2, new Scalar(0, 0, 255), 3, Imgproc.LINE_AA, 0);
        }

        // Display the result
        HighGui.imshow("Detected Lines", src);
        HighGui.waitKey();
        System.exit(0);
    }
}

需要注意的是，这里使用的是HoughLines函数而不是HoughLinesP函数。HoughLines函数可以检测出所有直线，而HoughLinesP函数只会检测出部分直线。