ORB描述符如何找到相似的图像？

Question

有2个图像，我为每个图像找到ORB描述符。接下来，我通过距离和RANSAC算法对描述符进行过滤，但事实证明并不是耳朵指示徽标等。问题是什么？

下面是代码：

public static void compareFeature(String filename1, String filename2) {
        ORB orb = ORB.create();

        DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);

        Mat img1 = Imgcodecs.imread(filename1, Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);
        Mat descriptors1 = new Mat();
        MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
        orb.detectAndCompute(img1, new Mat(), keypoints1, descriptors1);

// second image
        Mat img2 = Imgcodecs.imread(filename2, Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);
        Mat descriptors2 = new Mat();
        MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
        orb.detectAndCompute(img2, new Mat(), keypoints2, descriptors2);


// MATCHING
// match these two keypoints sets
        MatOfDMatch matches = new MatOfDMatch();
        matcher.match(descriptors1, descriptors2, matches);

        List<DMatch> matchesList = matches.toList();
        // ratio test
        LinkedList<DMatch> good_matches = new LinkedList<>();
        Double max_dist = 0.0;
        Double min_dist = 100.0;
        for (DMatch aMatchesList1 : matchesList) {
            Double dist = (double) aMatchesList1.distance;
            if (dist < min_dist)
                min_dist = dist;
            if (dist > max_dist)
                max_dist = dist;
        }
        for (DMatch aMatchesList : matchesList) {
            if (aMatchesList.distance <= (1.5 * min_dist))
                good_matches.addLast(aMatchesList);
        }
        // get keypoint coordinates of good matches to find homography and remove outliers using ransac
        List<Point> pts1 = new ArrayList<>();
        List<Point> pts2 = new ArrayList<>();
        for (DMatch good_matche : good_matches) {
            pts1.add(keypoints1.toList().get(good_matche.queryIdx).pt);
            pts2.add(keypoints2.toList().get(good_matche.trainIdx).pt);
        }

        // convertion of data types - there is maybe a more beautiful way
        Mat outputMask = new Mat();
        MatOfPoint2f pts1Mat = new MatOfPoint2f();
        pts1Mat.fromList(pts1);
        MatOfPoint2f pts2Mat = new MatOfPoint2f();
        pts2Mat.fromList(pts2);

        // Find homography - here just used to perform match filtering with RANSAC, but could be used to e.g. stitch images
        // the smaller the allowed reprojection error (here 15), the more matches are filtered
        System.out.println("pts1mat " + pts1Mat.size());
        System.out.println("pts2mat " + pts2Mat.size());
        Mat Homog = Calib3d.findHomography(pts1Mat, pts2Mat, Calib3d.RANSAC, 15, outputMask, 2000, 0.995);
        System.out.println("pts1mat " + pts1Mat.size());
        System.out.println("pts2mat " + pts2Mat.size());
        // outputMask contains zeros and ones indicating which matches are filtered
        LinkedList<DMatch> better_matches = new LinkedList<DMatch>();
        for (int i = 0; i < good_matches.size(); i++) {
            if (outputMask.get(i, 0)[0] != 0.0) {
                better_matches.add(good_matches.get(i));
            }
        }
        // DRAWING OUTPUT
        Mat outputImg = new Mat();
        // this will draw all matches, works fine
        MatOfDMatch better_matches_mat = new MatOfDMatch();
        better_matches_mat.fromList(better_matches);
        Features2d.drawMatches(img1, keypoints1, img2, keypoints2, better_matches_mat, outputImg);
        // save image
        Imgcodecs.imwrite("result.jpg", outputImg);
        System.out.println("better_matches_mat " + better_matches_mat.size());

它不能正常工作。告诉我要解决的问题，要解决的问题，以便一切正常。以及如何比较类似图像的描述符？