无法找到图像中对象的坐标

Question

我试图将图像中的对象的坐标附加到但无法获得：

此外，我正在获取图像的坐标。

Using the Probabilistic Hough Transform
Line spotted: 
     pt1: (124, 478)
Line spotted: 
     pt1: (638, 477)
Line spotted: 
     pt1: (490, 261)
Line spotted: 
     pt1: (559, 262)
Line spotted: 
     pt1: (492, 263)
Line spotted: 
     pt1: (557, 263)
Line spotted: 
     pt1: (36, 478)
Line spotted: 
     pt1: (215, 127)
Line spotted: 
     pt1: (254, 59)
Line spotted: 
     pt1: (216, 129)
Line spotted: 
     pt1: (215, 126)
Line spotted: 
     pt1: (253, 59)
Line spotted: 
     pt1: (493, 263)
Line spotted: 
     pt1: (215, 128)
Line spotted: 
     pt1: (493, 52)
Line spotted: 
     pt1: (189, 226)
Line spotted: 
     pt1: (493, 54)
Line spotted: 
     pt1: (276, 280)
Line spotted: 
     pt1: (493, 261)
Line spotted: 
     pt1: (317, 264)
Line spotted: 
     pt1: (300, 285)
Line spotted: 
     pt1: (165, 186)

但我无法预测这些坐标的图像，还需要图像中存在的三角形，矩形和圆形的倾斜角度。

以下是代码

public class HoughLines {

public static void main(String[] args) {

    String fileName = args.length >= 1 ? args[0] : "C:\\Users\\LENOVO\\Pictures\\24.png"; // if no params provided, compute the defaut image
   // args[1] ="probabilistic";
    IplImage src = cvLoadImage(fileName, 0);
    IplImage dst;
    IplImage colorDst;
    CvMemStorage storage = cvCreateMemStorage(0);
    CvSeq lines = new CvSeq();

    CanvasFrame source = new CanvasFrame("Source");
    CanvasFrame hough = new CanvasFrame("Hough");
    if (src == null) {
        System.out.println("Couldn't load source image.");
        return;
    }

    dst = cvCreateImage(cvGetSize(src), src.depth(), 1);
    colorDst = cvCreateImage(cvGetSize(src), src.depth(), 3);

    cvCanny(src, dst, 50, 200, 3);
    cvCvtColor(dst, colorDst, CV_GRAY2BGR);

    /*
     * apply the probabilistic hough transform
     * which returns for each line deteced two points ((x1, y1); (x2,y2))
     * defining the detected segment
     */
    if (true) { 
        System.out.println("Using the Probabilistic Hough Transform");
        lines = cvHoughLines2(dst, storage, CV_HOUGH_PROBABILISTIC, 1, Math.PI / 180, 40, 50, 10);
        for (int i = 0; i < lines.total(); i++) {
            // from JavaCPP, the equivalent of the C code:
            // CvPoint* line = (CvPoint*)cvGetSeqElem(lines,i);
            // CvPoint first=line[0], second=line[1]
            // is:
            // CvPoint first=line.position(0), secon=line.position(1);

            Pointer line = cvGetSeqElem(lines, i);
            CvPoint pt1  = new CvPoint(line).position(0);
            CvPoint pt2  = new CvPoint(line).position(1);

            System.out.println("Line spotted: ");
            System.out.println("\t pt1: " + pt1);
            //System.out.println("\t pt2: " + pt2);
            cvLine(colorDst, pt1, pt2, CV_RGB(255, 0, 0), 3, CV_AA, 0); // draw the segment on the image
        }
    }
    source.showImage(src);
    hough.showImage(colorDst);

    source.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
    hough.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
}
}

我也在添加原始图片：

Answer 1

有时你需要在cvHoughLines2之前应用一些模糊来做这种研究

使用方法：cvSmooth with Gaussian