关键点匹配只能工作两次......？ （java opencv）

我有一个非常奇怪的问题。我正在使用此代码来检测另一个代码中的图像（java opencv）：

更新的代码：

public void startRecognition() {
    //load images, I want to find img_object in img_scene
    Mat img_scene = Highgui.imread("D:/opencvws/ImageRecognition/src/main/resources/ascene.jpg");
    Mat img_object = Highgui.imread("D:/opencvws/ImageRecognition/src/main/resources/aobj1.jpg");
    run++;
    System.out.println("RUN NO: " + run);

    //init detector
    FeatureDetector detector = FeatureDetector.create(FeatureDetector.SURF);

    //keypoint detection for both images (keyponts_scene for img_scene, keypoint_object for img_object)
    MatOfKeyPoint keypoints_object = new MatOfKeyPoint();
    MatOfKeyPoint keypoints_scene  = new MatOfKeyPoint();
    detector.detect(img_object, keypoints_object);
    detector.detect(img_scene, keypoints_scene);
    System.out.println("OK: " + keypoints_object.total());
    System.out.println("SK: " + keypoints_scene.total());

    //extractor init
    DescriptorExtractor extractor = DescriptorExtractor.create(2); //2 = SURF;
    Mat descriptor_object = new Mat();
    Mat descriptor_scene = new Mat() ;
    //Compute descriptors
    extractor.compute(img_object, keypoints_object, descriptor_object);
    extractor.compute(img_scene, keypoints_scene, descriptor_scene);

    //init matcher
    DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED); // 1 = FLANNBASED
    matcher.clear();
    MatOfDMatch matches = new MatOfDMatch();

    //match both descriptors
    matcher.match(descriptor_object, descriptor_scene, matches);
    List<DMatch> matchesList = matches.toList();

    //calc min/max dist
    Double max_dist = 0.0;
    Double min_dist = 100.0;
    for(int i = 0; i < descriptor_object.rows(); i++){
        Double dist = (double) matchesList.get(i).distance;
        if(dist < min_dist) min_dist = dist;
        if(dist > max_dist) max_dist = dist;
    }

    //filter good matches
    LinkedList<DMatch> good_matches = new LinkedList<DMatch>();
    MatOfDMatch gm = new MatOfDMatch();

    //good match = distance > 2*min_distance ==> put them in a list
    for(int i = 0; i < descriptor_object.rows(); i++){
        if(matchesList.get(i).distance < 2*min_dist){
            good_matches.addLast(matchesList.get(i));
        }
    }
    //List -> Mat
    gm.fromList(good_matches);

    //mat for resulting image
    Mat img_matches = new Mat();

    //filter keypoints (use only good matches); First in a List, iterate, afterwards ==> Mat
    LinkedList<Point> objList = new LinkedList<Point>();
    LinkedList<Point> sceneList = new LinkedList<Point>();

    List<KeyPoint> keypoints_objectList = keypoints_object.toList();
    List<KeyPoint> keypoints_sceneList = keypoints_scene.toList();

    for(int i = 0; i<good_matches.size(); i++){
        objList.addLast(keypoints_objectList.get(good_matches.get(i).queryIdx).pt);
        sceneList.addLast(keypoints_sceneList.get(good_matches.get(i).trainIdx).pt);
    }

    MatOfPoint2f obj = new MatOfPoint2f();
    obj.fromList(objList);

    MatOfPoint2f scene = new MatOfPoint2f();
    scene.fromList(sceneList);

    //calc transformation matrix; method = 8 (RANSAC) ransacReprojThreshold=3
    Mat hg = Calib3d.findHomography(obj, scene, 8,3);

    //init corners
    Mat obj_corners = new Mat(4,1,CvType.CV_32FC2);
    Mat scene_corners = new Mat(4,1,CvType.CV_32FC2);
    //obj
    obj_corners.put(0, 0, new double[] {0,0});
    obj_corners.put(1, 0, new double[] {img_object.cols(),0});
    obj_corners.put(2, 0, new double[] {img_object.cols(),img_object.rows()});
    obj_corners.put(3, 0, new double[] {0,img_object.rows()});

    //transform obj corners to scene_img (stored in scene_corners)
    Core.perspectiveTransform(obj_corners,scene_corners, hg);

    //move points for img_obg width to the right to fit the matching image
    Point p1 = new Point(scene_corners.get(0,0)[0]+img_object.cols(), scene_corners.get(0,0)[1]);
    Point p2 = new Point(scene_corners.get(1,0)[0]+img_object.cols(), scene_corners.get(1,0)[1]);
    Point p3 = new Point(scene_corners.get(2,0)[0]+img_object.cols(), scene_corners.get(2,0)[1]);
    Point p4 = new Point(scene_corners.get(3,0)[0]+img_object.cols(), scene_corners.get(3,0)[1]);

    //create the matching image
    Features2d.drawMatches(
            img_object,
            keypoints_object, 
            img_scene,
            keypoints_scene, 
            gm, 
            img_matches);
    //draw lines to the matching image
    Core.line(img_matches, p1 , p2, new Scalar(0, 255, 0),4);
    Core.line(img_matches, p2, p3, new Scalar(0, 255, 0),4);
    Core.line(img_matches, p3, p4, new Scalar(0, 255, 0),4);
    Core.line(img_matches, p4, p1, new Scalar(0, 255, 0),4);


    // resizing...
    Mat resizeimage = new Mat();
    Size sz = new Size(1200, 1000);
    Imgproc.resize(img_matches, img_matches, sz);
    panel1.setimagewithMat(img_matches);

    frame1.repaint();

    //tried to prevent any old references to mix up new calculation 
    matcher.clear();
    img_matches = new Mat();
    img_object = new Mat();
    img_scene = new Mat();
    keypoints_object = new MatOfKeyPoint();
    keypoints_scene = new MatOfKeyPoint();
    hg = new Mat();
}

如果我在运行的应用程序中运行 startRecognition 方法两次（opencv 库在启动时加载），则两次识别都会得到相同的结果。对于第三次尝试，它检测其他关键点并计算另一个变换矩阵 (hg)。例子：

第二次尝试后：

第三次之后：

谁能解释为什么？或者告诉我如何预防？当我重新启动整个程序时，它会再次检测到两次正确，然后变化。经过几次尝试后，它将再次计算出正确的汞含量（根据第一次和第二次尝试）。我不明白为什么会发生这种情况。

提前致谢

gemorra