JavaCV 邊緣檢測方法與線圓檢測

1． 用OpenCV驗證常用邊緣檢測方法，

public class EdgeDetection {

    private final  static String path=System.getProperty("user.dir")+"\\catton.jpg";
    static{
        platformUtils.loadLibraries();
    }

    public static void main(String[] args) {
        Mat srcimage;
        //讀取一張灰度圖片
        srcimage= Imgcodecs.imread(path,Imgcodecs.IMREAD_COLOR);
        if (srcimage.empty()) {
            System.err.println("加載圖片出錯，請檢查圖片路徑！");
            return;
        }
        System.out.println(srcimage);
        // 索貝爾水平檢測 邊緣檢測
       // Imgproc.Sobel(srcimage,dstimg, CvType.CV_8UC1,1, 0);

        //索貝爾垂直檢測
        Mat Sobel_dstimg=new Mat();
       // Imgproc.Sobel(srcimage, dstimg, CvType.CV_8UC1,0, 1);

        // Canny 邊緣檢測
        Mat canny_dstimg=new Mat();
        Imgproc.Canny(srcimage,canny_dstimg,50,240);

        //拉普拉斯邊檢測
        Mat laplacian_dstimg=new Mat();
        Imgproc.Laplacian(srcimage,laplacian_dstimg,CvType.CV_8UC1);

        HighGui.imshow("邊緣檢測 原圖像",srcimage);
        HighGui.imshow("邊緣檢測 Canny輸出圖像",canny_dstimg);
        HighGui.imshow("邊緣檢測 Laplacian輸出圖像",laplacian_dstimg);
        // 無限等待按鍵按下
        HighGui.waitKey(0);
    }
}

2． 用OpenCV驗證Hough變換檢測圖像中的直線或圓

package com.gitee.dgw.lesson9;

import com.gitee.dgw.lesson1.platformUtils;
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;



/**
 * @program: learn-opencv
 * @description:
 * @author: Mr.Dai
 * @create: 2020-04-10 22:01
 **/
public class HoughDetect {

    private final  static String path=System.getProperty("user.dir")+"\\line.png";
    static{
        platformUtils.loadLibraries();
    }
    public static void main(String[] args) {

        Mat srcimage;
        //讀取一張灰度圖片
        srcimage= Imgcodecs.imread(path,Imgcodecs.IMREAD_COLOR);
        if (srcimage.empty()) {
            System.err.println("加載圖片出錯，請檢查圖片路徑！");
            return;
        }
        System.out.println(srcimage);
        Mat dst_img=srcimage.clone();
        Imgproc.Canny(srcimage, dst_img, 200, 500, 5, false);

        Imgproc.cvtColor(srcimage,dst_img,Imgproc.COLOR_RGB2GRAY);
        //dectCircle(srcimage, dst_img);
        Mat storage = new Mat();
        Imgproc.HoughLinesP(dst_img, storage, 1, Math.PI / 180, 50, 0, 0);
        for (int x = 0; x < storage.rows(); x++)
        {
            double[] vec = storage.get(x, 0);
            double x1 = vec[0], y1 = vec[1], x2 = vec[2], y2 = vec[3];
            Point start = new Point(x1, y1);
            Point end = new Point(x2, y2);
            Imgproc.line(srcimage, start, end, new Scalar(0, 0, 255, 255), 1, Imgproc.LINE_4, 0);
        }
        HighGui.imshow("邊緣檢測 原圖像",dst_img);
        HighGui.imshow("邊緣檢測 Canny輸出圖像",srcimage);
        // 無限等待按鍵按下
        HighGui.waitKey(0);
    }

    private static void dectCircle(Mat srcimage, Mat dst_img) {
        Mat circles = new Mat();
        Imgproc.HoughCircles(dst_img, circles, Imgproc.HOUGH_GRADIENT, 1, 100, 440, 50, 0, 345);
        //概率霍夫變換）
        for (int i = 0; i < circles.cols(); i++)
        {
            double[] vCircle = circles.get(0, i);
            Point center = new Point(vCircle[0], vCircle[1]);
            int radius = (int) Math.round(vCircle[2]);
            // circle center
            Imgproc.circle(srcimage, center, 3, new Scalar(0, 255, 0), -1, 8, 0);
            // circle outline
            Imgproc.circle(srcimage, center, radius, new Scalar(0, 0, 255), 3, 8, 0);
        }
    }
}