There are 2 images, I find ORB descriptors for each of them. Next, I filter the descriptors by distance and by the RANSAC algorithm, but it turns out not that the ear indicates the logo and so on. What is the problem?
Below is the code:
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 eg 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()); } 