import java.util.ArrayList; import java.util.List; import org.opencv.core.Core; import org.opencv.core.DMatch; import org.opencv.core.Mat; import org.opencv.core.MatOfByte; import org.opencv.core.MatOfDMatch; import org.opencv.core.MatOfKeyPoint; import org.opencv.core.Scalar; import org.opencv.features2d.DescriptorMatcher; import org.opencv.features2d.Features2d; import org.opencv.highgui.HighGui; import org.opencv.imgcodecs.Imgcodecs; import org.opencv.xfeatures2d.SURF; class SURFFLANNMatching { public void run(String[] args) { String filename1 = args.length > 1 ? args[0] : "../data/box.png"; String filename2 = args.length > 1 ? args[1] : "../data/box_in_scene.png"; Mat img1 = Imgcodecs.imread(filename1, Imgcodecs.IMREAD_GRAYSCALE); Mat img2 = Imgcodecs.imread(filename2, Imgcodecs.IMREAD_GRAYSCALE); if (img1.empty() || img2.empty()) { System.err.println("Cannot read images!"); System.exit(0); } //-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors double hessianThreshold = 400; int nOctaves = 4, nOctaveLayers = 3; boolean extended = false, upright = false; SURF detector = SURF.create(hessianThreshold, nOctaves, nOctaveLayers, extended, upright); MatOfKeyPoint keypoints1 = new MatOfKeyPoint(), keypoints2 = new MatOfKeyPoint(); Mat descriptors1 = new Mat(), descriptors2 = new Mat(); detector.detectAndCompute(img1, new Mat(), keypoints1, descriptors1); detector.detectAndCompute(img2, new Mat(), keypoints2, descriptors2); //-- Step 2: Matching descriptor vectors with a FLANN based matcher // Since SURF is a floating-point descriptor NORM_L2 is used DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED); List<MatOfDMatch> knnMatches = new ArrayList<>(); matcher.knnMatch(descriptors1, descriptors2, knnMatches, 2); //-- Filter matches using the Lowe's ratio test float ratioThresh = 0.7f; List<DMatch> listOfGoodMatches = new ArrayList<>(); for (int i = 0; i < knnMatches.size(); i++) { if (knnMatches.get(i).rows() > 1) { DMatch[] matches = knnMatches.get(i).toArray(); if (matches[0].distance < ratioThresh * matches[1].distance) { listOfGoodMatches.add(matches[0]); } } } MatOfDMatch goodMatches = new MatOfDMatch(); goodMatches.fromList(listOfGoodMatches); //-- Draw matches Mat imgMatches = new Mat(); Features2d.drawMatches(img1, keypoints1, img2, keypoints2, goodMatches, imgMatches, Scalar.all(-1), Scalar.all(-1), new MatOfByte(), Features2d.NOT_DRAW_SINGLE_POINTS); //-- Show detected matches HighGui.imshow("Good Matches", imgMatches); HighGui.waitKey(0); System.exit(0); } } public class SURFFLANNMatchingDemo { public static void main(String[] args) { // Load the native OpenCV library System.loadLibrary(Core.NATIVE_LIBRARY_NAME); new SURFFLANNMatching().run(args); } }