比较旋转图像

我正在寻找一种方法来比较几乎相同（相似度超过 95%）但可以绕中心轴旋转的图像。

我对整个计算机图形/视觉领域很陌生，不太确定是否有现成的工具或系统，或者即使这是否是正确的堆栈交换。

目前，我正在研究使用 C# 生成位图直方图，然后通过 Panda 运行它进行分析，并根据直方图的相似性对图像进行理想的分组，尽管我听说 OpenCv + tesseract 之类的东西可能是一个可行的替代方案。

您需要计算两个图像之间的仿射变换矩阵，以便获取有关缩放、平移和rotation.

这个矩阵看起来怎么样以及如何获得旋转差？

从这个答案：

我用过以下Java代码（使用 OpenCV 3.2）计算scaling, 翻译 and rotation两个 Mat 图像之间的差异。我希望你会发现它很有用。

static void calculateDifferences(Mat img1, Mat img2){

        // Initialization
        FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
        DescriptorExtractor descriptor = DescriptorExtractor.create(DescriptorExtractor.ORB);
        DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);

        // First image objects
        Mat img1_descriptors = new Mat();
        MatOfKeyPoint img1_keypoints_mat = new MatOfKeyPoint();

        // Detect KeyPoints for first image
        detector.detect(img1, img1_keypoints_mat);
        descriptor.compute(img1, img1_keypoints_mat, img1_descriptors);

        // Second image objects
        Mat img2_descriptors = new Mat();
        MatOfKeyPoint img2_keypoints_mat = new MatOfKeyPoint();

        // Detect KeyPoints for second image
        detector.detect(img2, img2_keypoints_mat);
        descriptor.compute(img2, img2_keypoints_mat, img2_descriptors);

        // Match KeyPoints
        MatOfDMatch matOfDMatch = new MatOfDMatch();
        matcher.match(img1_descriptors, img2_descriptors, matOfDMatch);

        // Filtering the matches
        List<DMatch> dMatchList = matOfDMatch.toList();
        Double max_dist = 0.0;
        Double min_dist = 100.0;

        for(int i = 0; i < img1_descriptors.rows(); i++){
            Double dist = (double) dMatchList.get(i).distance;
            if(dist < min_dist) min_dist = dist;
            if(dist > max_dist) max_dist = dist;
        }
        LinkedList<DMatch> good_matches = new LinkedList<>();
        for(int i = 0; i < img1_descriptors.rows(); i++){
            if(dMatchList.get(i).distance < 3*min_dist){
                good_matches.addLast(dMatchList.get(i));
            }
        }

        // Converting to MatOfPoint2f format
        LinkedList<Point> img1_points_list = new LinkedList<>();
        LinkedList<Point> img2_points_list = new LinkedList<>();

        List<KeyPoint> img1_keyPoints_list = img1_keypoints_mat.toList();
        List<KeyPoint> img2_keyPoints_list = img2_keypoints_mat.toList();

        int limit = good_matches.size();
        for(int i = 0; i < limit; i++){
            img1_points_list.addLast(img1_keyPoints_list.get(good_matches.get(i).queryIdx).pt);
            img2_points_list.addLast(img2_keyPoints_list.get(good_matches.get(i).trainIdx).pt);
        }

        MatOfPoint2f img1_point2f_mat = new MatOfPoint2f();
        img1_point2f_mat.fromList(img1_points_list);

        MatOfPoint2f img2_point2f_mat = new MatOfPoint2f();
        img2_point2f_mat.fromList(img2_points_list);

        // Computing the affine transform matrix
        Mat result = Video.estimateRigidTransform(img1_point2f_mat, img2_point2f_mat, true);
        printMat(result); // Printing the optimal affine transformation 2x3 array

        // The following variables correspond to the estimateRigidTransform result as shown here: https://stackoverflow.com/a/29511091/5165833
        double a = result.get(0,0)[0];
        double b = result.get(0,1)[0];
        double d = result.get(1,1)[0];
        double c = result.get(1,0)[0];
        double tx = result.get(0,2)[0];
        double ty = result.get(1,2)[0];

        // Solving for scale,translation and rotation as shown in the link above
        double scale_x = Math.signum(a) * Math.sqrt( (a*a) + (b*b) ); // Axis x scale difference
        double scale_y = Math.signum(d) * Math.sqrt( (c*c) + (d*d) ); // Axis y scale difference
        double translation = ty; // The translation difference
        double rotation_angle = Math.atan2(c,d); // Rotation difference

        // Printing results
        println("Scale_x diff: " + scale_x);
        println("Scale_y diff: " + scale_y);
        println("Translation diff: " + translation);
        println("Rotation diff: " + rotation_angle);
    }

    static void printMat(Mat m)
    {
        for (int x=0; x < m.height(); x++) {
            for (int y=0; y < m.width(); y++) {
                System.out.printf("%f",m.get(x,y)[0]);
                System.out.printf("%s"," ");
            }
            System.out.println();
        }
    }