MMOSX's profile - activity

Hi, i want this:

but i obtain this with my code:

and my code is:

Bitmap Matches(){

        Mat images1 = new Mat();
        Mat images2 = new Mat();
        images1 = immagine1.clone();
        images2 = immagine2.clone();

        // trovo i keypoint
        final MatOfKeyPoint keypoint1 = new MatOfKeyPoint();
        final MatOfKeyPoint keypoint2 = new MatOfKeyPoint();
        final Mat descriptor1 = new Mat();
        final Mat descriptor2 = new Mat();
        final Mat out_put_image = new Mat();
        Bitmap image;
        final MatOfDMatch dMatch = new MatOfDMatch();

        FeatureDetector detector = FeatureDetector.create(FeatureDetector.BRISK);
        final DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.BRISK);
        final DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);

        detector.detect(images1, keypoint1);
        detector.detect(images2, keypoint2);

        // trovo i descrittori
        descriptorExtractor.compute(images1, keypoint1, descriptor1);
        descriptorExtractor.compute(images2, keypoint2, descriptor2);

        // trovo i match
        matcher.match(descriptor2, descriptor1, dMatch);

        //calculate max and min distances between keypoints
        double max_dist=0;double min_dist=99;

        List<DMatch> matchesList = dMatch.toList();
        for(int i=0;i<descriptor2.rows();i++)
        {
            double dist = matchesList.get(i).distance;

            if (dist < min_dist && dist != 0)
            {
                min_dist = dist;
            }

            if (dist > max_dist)
            {
                max_dist = dist;
            }
        }

        double threshold = 3 * min_dist;
        double threshold2 = 2 * min_dist;

        if (threshold2 >= max_dist)
        {
            threshold = min_dist * 1.1;
        }
        else if (threshold >= max_dist)
        {
            threshold = threshold2 * 1.4;
        }

        //set up good matches, add matches if close enough
        LinkedList<DMatch> good_matches = new LinkedList<DMatch>();
        MatOfDMatch gm = new MatOfDMatch();

        for (int i = 0; i < matchesList.size(); i++)
        {
            double dist = matchesList.get(i).distance;
            if (dist < threshold)
            {
                good_matches.add(dMatch.toList().get(i));
            }
        }
        gm.fromList(good_matches);

        //put keypoints mats into lists
        List<KeyPoint> keypoints1_List = keypoint1.toList();
        List<KeyPoint> keypoints2_List = keypoint2.toList();

        //put keypoints into point2f mats so calib3d can use them to find homography
        LinkedList<Point> objList = new LinkedList<Point>();
        LinkedList<KeyPoint> objK = new LinkedList<>();
        LinkedList<Point> sceneList = new LinkedList<Point>();
        LinkedList<KeyPoint> scnK = new LinkedList<>();
        for(int i=0;i<good_matches.size();i++)
        {
            objList.addLast(keypoints1_List.get(good_matches.get(i).trainIdx).pt);
            objK.add(keypoints1_List.get(good_matches.get(i).trainIdx));
            sceneList.addLast(keypoints2_List.get(good_matches.get(i).queryIdx).pt);
            scnK.addLast(keypoints2_List.get(good_matches.get(i).queryIdx));
        }
        MatOfPoint2f obj = new MatOfPoint2f();
        MatOfPoint2f scene = new MatOfPoint2f();
        obj.fromList(objList);
        scene.fromList(sceneList);

        //run homography on object and scene points
        Mat H = Calib3d.findHomography(obj, scene, Calib3d.RANSAC, 0.001);

        // Trovo i contorni:
        Mat gray1 = new Mat();
        Mat hierarchy = new Mat();
        Mat cannyEdges = new Mat();
        List<MatOfPoint> contourList = new ArrayList<>();

        Imgproc.cvtColor(images1, gray1, Imgproc.COLOR_BGR2GRAY);
        Imgproc.Canny(images1, cannyEdges, 10, 110);

        Imgproc.findContours(cannyEdges, contourList, hierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);

        Mat obj_mat = Converters.vector_Point_to_Mat(contourList.get(0).toList(),CvType.CV_32F);
        Mat destination = new Mat(obj_mat.rows(),obj_mat.cols(),CvType.CV_32F);

        List<MatOfPoint> contourLists = new ArrayList<>();

        //Creo l'immagine
        Imgproc.cvtColor(images1, images1, Imgproc.COLOR_BGR2RGB);
        Imgproc.cvtColor(images2, images2, Imgproc.COLOR_BGR2RGB);
        MatOfPoint2f approxCurve = new MatOfPoint2f();

        //For each contour found
        for (int i=0; i<contourList.size(); i++)
        {
            //Convert contours(i) from MatOfPoint to MatOfPoint2f
            MatOfPoint2f contour2f = new MatOfPoint2f( contourList.get(i).toArray() );
            //Processing on mMOP2f1 which is in type MatOfPoint2f
            double approxDistance = Imgproc.arcLength(contour2f, true)*0.02;
            Imgproc.approxPolyDP(contour2f, approxCurve, approxDistance, true);

            //Convert back to MatOfPoint
            MatOfPoint points = new MatOfPoint( approxCurve.toArray() );

            // Get bounding rect of contour
            Rect ...

HI, I find the keypoint and the match between two images with BRISK ( I have to use it ) but now I need to use RANSAC to estimate the correspondence better than the only matcher function. Can you help me?

I think: I take the position of keypoint in the object and in the scene and calculate Homography with it, but i don't now how to continue.

Please help me.

This is my code:

Bitmap Matches(){
    FeatureDetector detector;
    MatOfKeyPoint keypoints1, keypoints2;
    DescriptorExtractor descriptorExtractor;
    Mat descriptors1, descriptors2;
    DescriptorMatcher descriptorMatcher;
    MatOfDMatch matches = new MatOfDMatch();
    keypoints1 = new MatOfKeyPoint();
    keypoints2 = new MatOfKeyPoint();
    descriptors1 = new Mat();
    descriptors2 = new Mat();
    detector = FeatureDetector.create(FeatureDetector.BRISK);
    descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.BRISK);
    descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
    detector.detect(immagine1,keypoints1);
    detector.detect(immagine2, keypoints2);

    descriptorExtractor.compute(immagine1, keypoints1, descriptors1);
    descriptorExtractor.compute(immagine2, keypoints2, descriptors2);
    descriptorMatcher.match(descriptors2, descriptors1, matches);

    //calculate max and min distances between keypoints
    double max_dist=0;double min_dist=99;

    List<DMatch> matchesList = matches.toList();
    for(int i=0;i<descriptors2.rows();i++)
    {
        double dist = matchesList.get(i).distance;
        if (dist<min_dist) min_dist = dist;
        if (dist>max_dist) max_dist = dist;
    }

    //set up good matches, add matches if close enough
    LinkedList<DMatch> good_matches = new LinkedList<DMatch>();
    MatOfDMatch gm = new MatOfDMatch();
    for (int i=0;i<descriptors1.rows();i++)
    {
        if(matchesList.get(i).distance<max_dist)
        {
            good_matches.addLast(matchesList.get(i));
        }
    }
    gm.fromList(good_matches);

    //put keypoints mats into lists
    List<KeyPoint> keypoints1_List = keypoints1.toList();
    List<KeyPoint> keypoints2_List = keypoints2.toList();

    //put keypoints into point2f mats so calib3d can use them to find homography
    LinkedList<Point> objList = new LinkedList<Point>();
    LinkedList<Point> sceneList = new LinkedList<Point>();
    for(int i=0;i<good_matches.size();i++)
    {
        objList.addLast(keypoints1_List.get(good_matches.get(i).trainIdx).pt);
        sceneList.addLast(keypoints2_List.get(good_matches.get(i).queryIdx).pt);
    }
    MatOfPoint2f obj = new MatOfPoint2f();
    MatOfPoint2f scene = new MatOfPoint2f();
    obj.fromList(objList);
    scene.fromList(sceneList);

    //output image
    Mat outputImg = new Mat();
    MatOfByte drawnMatches = new MatOfByte();
    Features2d.drawMatches(immagine1, keypoints1, immagine2, keypoints2, gm, outputImg,
            Scalar.all(-1), Scalar.all(-1), drawnMatches,Features2d.NOT_DRAW_SINGLE_POINTS);

    //run homography on object and scene points
    Mat H = Calib3d.findHomography(obj, scene,Calib3d.RANSAC, 10);


    // trovo il contorno dell'oggetto
    Mat edges = new Mat();
    Mat hierarchy = new Mat();

    // ogni contorno è una lista di punti
    List<MatOfPoint> contourList = new ArrayList<MatOfPoint>(); // lista dei contorni

    Imgproc.Canny(immagine1_grey, edges, 10, 100);
    // Applico la trasformazione all'immagine
    Mat bordi = new Mat(edges.cols(),edges.rows(),CvType.CV_32FC2);
    //Trovo i contorni
    Imgproc.findContours(edges,contourList,hierarchy,Imgproc.RETR_LIST,Imgproc.CHAIN_APPROX_SIMPLE);

    MatOfPoint2f approxCurve = new MatOfPoint2f();
    MatOfPoint points = null;
    //For each contour found
    for (int i=0; i<contourList.size(); i++)
    {
        //Convert contours(i) from MatOfPoint to MatOfPoint2f
        MatOfPoint2f contour2f = new MatOfPoint2f( contourList.get(i).toArray() );
        //Processing on mMOP2f1 which is in type MatOfPoint2f
        double approxDistance = Imgproc.arcLength(contour2f, true)*0.02;
        Imgproc.approxPolyDP(contour2f, approxCurve, approxDistance, true);

        //Convert back to MatOfPoint
        points = new MatOfPoint( approxCurve.toArray() );

        // Get bounding rect of contour
        Rect rect = Imgproc.boundingRect(points);

        // draw enclosing rectangle (all same color, but you could use variable i to make them ...