Example usage for org.opencv.features2d DescriptorExtractor SIFT

Introduction

In this page you can find the example usage for org.opencv.features2d DescriptorExtractor SIFT.

Prototype

int SIFT

To view the source code for org.opencv.features2d DescriptorExtractor SIFT.

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Usage

From source file:net.semanticmetadata.lire.imageanalysis.features.local.opencvfeatures.CvSiftExtractor.java

License:Open Source License

private void init() {
    System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

    detector = FeatureDetector.create(FeatureDetector.SIFT);
    extractor = DescriptorExtractor.create(DescriptorExtractor.SIFT);
    //        if (passingParams) {
    try {/*from   w w  w.j av a 2  s . c  o  m*/
        File temp = File.createTempFile("tempFile", ".tmp");
        //int nfeatures=0, int nOctaveLayers=3, double contrastThreshold=0.04, double edgeThreshold=10, double sigma=1.6
        //String settings = "%YAML:1.0\nnfeatures: 0\nnOctaveLayers: 3\ncontrastThreshold: 0.04\nedgeThreshold: 10\nsigma: 1.6";
        String settings = "%YAML:1.0\nnfeatures: " + nfeatures + "\nnOctaveLayers: " + nOctaveLayers
                + "\ncontrastThreshold: " + contrastThreshold + "\nedgeThreshold: " + edgeThreshold
                + "\nsigma: " + sigma;
        FileWriter writer = new FileWriter(temp, false);
        writer.write(settings);
        writer.close();
        extractor.read(temp.getPath());
        detector.read(temp.getPath());
        temp.deleteOnExit();
    } catch (IOException e) {
        e.printStackTrace();
    }
    //        }
}

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From source file:Recognizer.Recognizer.java

public void SIFT(Image imQ, Image imDB) {
    Mat Q = imQ.Image1CtoMat_CV();
    Mat DB = imDB.Image1CtoMat_CV();

    Mat matQ = new Mat();
    Mat matDB = new Mat();

    Q.convertTo(matQ, CvType.CV_8U);/* w  w w. ja v a 2 s. c om*/
    DB.convertTo(matDB, CvType.CV_8U);

    FeatureDetector siftDet = FeatureDetector.create(FeatureDetector.SIFT);
    DescriptorExtractor siftExt = DescriptorExtractor.create(DescriptorExtractor.SIFT);

    MatOfKeyPoint kpQ = new MatOfKeyPoint();
    MatOfKeyPoint kpDB = new MatOfKeyPoint();

    siftDet.detect(matQ, kpQ);
    siftDet.detect(matDB, kpDB);

    Mat matDescriptorQ = new Mat(matQ.rows(), matQ.cols(), matQ.type());
    Mat matDescriptorDB = new Mat(matDB.rows(), matDB.cols(), matDB.type());

    siftExt.compute(matQ, kpQ, matDescriptorQ);
    siftExt.compute(matDB, kpDB, matDescriptorDB);

    MatOfDMatch matchs = new MatOfDMatch();

    DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE);

    matcher.match(matDescriptorQ, matDescriptorDB, matchs);

    int N = 10;

    DMatch[] tmp01 = matchs.toArray();
    DMatch[] tmp02 = new DMatch[N];

    for (int i = 0; i < tmp02.length; i++) {
        tmp02[i] = tmp01[i];
    }

    matchs.fromArray(tmp02);

    Mat matchedImage = new Mat(matQ.rows(), matQ.cols() * 2, matQ.type());
    Features2d.drawMatches(matQ, kpQ, matDB, kpDB, matchs, matchedImage);

    Highgui.imwrite("./descriptedImageBySIFT.jpg", matchedImage);

}

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From source file:View.Signature.java

public static int sift(String routeVal, String route, String n_img1, String n_img2, String extension) {

    String bookObject = routeVal + n_img2 + extension;
    String bookScene = route + n_img1 + extension;

    //System.out.println("Iniciando SIFT");
    //java.lang.System.out.print("Abriendo imagenes | ");
    Mat objectImage = Highgui.imread(bookObject, Highgui.CV_LOAD_IMAGE_COLOR);
    Mat sceneImage = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR);

    MatOfKeyPoint objectKeyPoints = new MatOfKeyPoint();
    FeatureDetector featureDetector = FeatureDetector.create(FeatureDetector.SIFT);
    //java.lang.System.out.print("Encontrar keypoints con SIFT | ");  
    featureDetector.detect(objectImage, objectKeyPoints);
    KeyPoint[] keypoints = objectKeyPoints.toArray();

    MatOfKeyPoint objectDescriptors = new MatOfKeyPoint();
    DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.SIFT);
    //java.lang.System.out.print("Computando descriptores | ");  
    descriptorExtractor.compute(objectImage, objectKeyPoints, objectDescriptors);

    // Create the matrix for output image.   
    Mat outputImage = new Mat(objectImage.rows(), objectImage.cols(), Highgui.CV_LOAD_IMAGE_COLOR);
    Scalar newKeypointColor = new Scalar(255, 0, 0);

    //java.lang.System.out.print("Dibujando keypoints en imagen base | ");  
    Features2d.drawKeypoints(objectImage, objectKeyPoints, outputImage, newKeypointColor, 0);

    // Match object image with the scene image  
    MatOfKeyPoint sceneKeyPoints = new MatOfKeyPoint();
    MatOfKeyPoint sceneDescriptors = new MatOfKeyPoint();
    //java.lang.System.out.print("Detectando keypoints en imagen base | ");
    featureDetector.detect(sceneImage, sceneKeyPoints);
    //java.lang.System.out.print("Computando descriptores en imagen base | ");
    descriptorExtractor.compute(sceneImage, sceneKeyPoints, sceneDescriptors);

    Mat matchoutput = new Mat(sceneImage.rows() * 2, sceneImage.cols() * 2, Highgui.CV_LOAD_IMAGE_COLOR);
    Scalar matchestColor = new Scalar(0, 255, 0);

    List<MatOfDMatch> matches = new LinkedList<MatOfDMatch>();
    DescriptorMatcher descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED);
    //java.lang.System.out.print("Encontrando matches entre imagenes | ");  
    descriptorMatcher.knnMatch(objectDescriptors, sceneDescriptors, matches, 2);

    //java.lang.System.out.println("Calculando buenos matches");
    LinkedList<DMatch> goodMatchesList = new LinkedList<DMatch>();

    float nndrRatio = 0.7f;
    java.lang.System.out.println(matches.size());
    for (int i = 0; i < matches.size(); i++) {
        MatOfDMatch matofDMatch = matches.get(i);
        DMatch[] dmatcharray = matofDMatch.toArray();
        DMatch m1 = dmatcharray[0];//from  www  . j  a v  a2  s .c  o m
        DMatch m2 = dmatcharray[1];

        if (m1.distance <= m2.distance * nndrRatio) {
            goodMatchesList.addLast(m1);

        }
    }

    if (goodMatchesList.size() >= 7) {
        //java.lang.System.out.println("Match enontrado!!! Matches: "+goodMatchesList.size());
        //if(goodMatchesList.size()>max){

        //cambio = 1;
        //}    

        List<KeyPoint> objKeypointlist = objectKeyPoints.toList();
        List<KeyPoint> scnKeypointlist = sceneKeyPoints.toList();

        LinkedList<Point> objectPoints = new LinkedList<>();
        LinkedList<Point> scenePoints = new LinkedList<>();

        for (int i = 0; i < goodMatchesList.size(); i++) {
            objectPoints.addLast(objKeypointlist.get(goodMatchesList.get(i).queryIdx).pt);
            scenePoints.addLast(scnKeypointlist.get(goodMatchesList.get(i).trainIdx).pt);
        }

        MatOfPoint2f objMatOfPoint2f = new MatOfPoint2f();
        objMatOfPoint2f.fromList(objectPoints);
        MatOfPoint2f scnMatOfPoint2f = new MatOfPoint2f();
        scnMatOfPoint2f.fromList(scenePoints);

        Mat homography = Calib3d.findHomography(objMatOfPoint2f, scnMatOfPoint2f, Calib3d.RANSAC, 3);

        Mat obj_corners = new Mat(4, 1, CvType.CV_32FC2);
        Mat scene_corners = new Mat(4, 1, CvType.CV_32FC2);

        obj_corners.put(0, 0, new double[] { 0, 0 });
        obj_corners.put(1, 0, new double[] { objectImage.cols(), 0 });
        obj_corners.put(2, 0, new double[] { objectImage.cols(), objectImage.rows() });
        obj_corners.put(3, 0, new double[] { 0, objectImage.rows() });

        //System.out.println("Transforming object corners to scene corners...");  
        Core.perspectiveTransform(obj_corners, scene_corners, homography);

        Mat img = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR);

        Core.line(img, new Point(scene_corners.get(0, 0)), new Point(scene_corners.get(1, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(1, 0)), new Point(scene_corners.get(2, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(2, 0)), new Point(scene_corners.get(3, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(3, 0)), new Point(scene_corners.get(0, 0)),
                new Scalar(0, 255, 0), 4);

        //java.lang.System.out.println("Dibujando imagen de coincidencias");
        MatOfDMatch goodMatches = new MatOfDMatch();
        goodMatches.fromList(goodMatchesList);

        Features2d.drawMatches(objectImage, objectKeyPoints, sceneImage, sceneKeyPoints, goodMatches,
                matchoutput, matchestColor, newKeypointColor, new MatOfByte(), 2);
        String n_outputImage = route + "results\\" + n_img2 + "_outputImage_sift" + extension;
        String n_matchoutput = route + "results\\" + n_img2 + "_matchoutput_sift" + extension;
        String n_img = route + "results\\" + n_img2 + "_sift" + extension;
        Highgui.imwrite(n_outputImage, outputImage);
        Highgui.imwrite(n_matchoutput, matchoutput);
        //Highgui.imwrite(n_img, img);  
        java.lang.System.out.println(goodMatches.size().height);
        double result = goodMatches.size().height * 100 / matches.size();

        java.lang.System.out.println((int) result);
        //double result =goodMatches.size().height;
        if (result > 100) {
            return 100;
        } else if (result <= 100 && result > 85) {
            return 85;
        } else if (result <= 85 && result > 50) {
            return 50;
        } else if (result <= 50 && result > 25) {
            return 25;
        } else {
            return 0;
        }
    } else {
        //java.lang.System.out.println("Firma no encontrada");  
    }
    return 0;
    //System.out.println("Terminando SIFT");  
}

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From source file:View.SignatureLib.java

public static int sift(String routeRNV, String routeAdherent) {

    String bookObject = routeAdherent;
    String bookScene = routeRNV;/*from w  w  w . ja  v a 2 s.  c  om*/

    //System.out.println("Iniciando SIFT");
    //java.lang.System.out.print("Abriendo imagenes | ");
    Mat objectImage = Highgui.imread(bookObject, Highgui.CV_LOAD_IMAGE_COLOR);
    Mat sceneImage = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR);

    MatOfKeyPoint objectKeyPoints = new MatOfKeyPoint();
    FeatureDetector featureDetector = FeatureDetector.create(FeatureDetector.SIFT);
    //java.lang.System.out.print("Encontrar keypoints con SIFT | ");  
    featureDetector.detect(objectImage, objectKeyPoints);
    KeyPoint[] keypoints = objectKeyPoints.toArray();

    MatOfKeyPoint objectDescriptors = new MatOfKeyPoint();
    DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.SIFT);
    //java.lang.System.out.print("Computando descriptores | ");  
    descriptorExtractor.compute(objectImage, objectKeyPoints, objectDescriptors);

    // Create the matrix for output image.   
    Mat outputImage = new Mat(objectImage.rows(), objectImage.cols(), Highgui.CV_LOAD_IMAGE_COLOR);
    Scalar newKeypointColor = new Scalar(255, 0, 0);

    //java.lang.System.out.print("Dibujando keypoints en imagen base | ");  
    Features2d.drawKeypoints(objectImage, objectKeyPoints, outputImage, newKeypointColor, 0);

    // Match object image with the scene image  
    MatOfKeyPoint sceneKeyPoints = new MatOfKeyPoint();
    MatOfKeyPoint sceneDescriptors = new MatOfKeyPoint();
    //java.lang.System.out.print("Detectando keypoints en imagen base | ");
    featureDetector.detect(sceneImage, sceneKeyPoints);
    //java.lang.System.out.print("Computando descriptores en imagen base | ");
    descriptorExtractor.compute(sceneImage, sceneKeyPoints, sceneDescriptors);

    Mat matchoutput = new Mat(sceneImage.rows() * 2, sceneImage.cols() * 2, Highgui.CV_LOAD_IMAGE_COLOR);
    Scalar matchestColor = new Scalar(0, 255, 0);

    List<MatOfDMatch> matches = new LinkedList<MatOfDMatch>();
    DescriptorMatcher descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED);
    //java.lang.System.out.println(sceneDescriptors);  

    if (sceneDescriptors.empty()) {
        java.lang.System.out.println("Objeto no encontrado");
        return 0;
    }

    descriptorMatcher.knnMatch(objectDescriptors, sceneDescriptors, matches, 2);

    //java.lang.System.out.println("Calculando buenos matches");
    LinkedList<DMatch> goodMatchesList = new LinkedList<DMatch>();

    float nndrRatio = 0.7f;

    for (int i = 0; i < matches.size(); i++) {
        MatOfDMatch matofDMatch = matches.get(i);
        DMatch[] dmatcharray = matofDMatch.toArray();
        DMatch m1 = dmatcharray[0];
        DMatch m2 = dmatcharray[1];

        if (m1.distance <= m2.distance * nndrRatio) {
            goodMatchesList.addLast(m1);

        }
    }

    if (goodMatchesList.size() >= 7) {
        max = goodMatchesList.size();

        List<KeyPoint> objKeypointlist = objectKeyPoints.toList();
        List<KeyPoint> scnKeypointlist = sceneKeyPoints.toList();

        LinkedList<Point> objectPoints = new LinkedList<>();
        LinkedList<Point> scenePoints = new LinkedList<>();

        for (int i = 0; i < goodMatchesList.size(); i++) {
            objectPoints.addLast(objKeypointlist.get(goodMatchesList.get(i).queryIdx).pt);
            scenePoints.addLast(scnKeypointlist.get(goodMatchesList.get(i).trainIdx).pt);
        }

        MatOfPoint2f objMatOfPoint2f = new MatOfPoint2f();
        objMatOfPoint2f.fromList(objectPoints);
        MatOfPoint2f scnMatOfPoint2f = new MatOfPoint2f();
        scnMatOfPoint2f.fromList(scenePoints);

        Mat homography = Calib3d.findHomography(objMatOfPoint2f, scnMatOfPoint2f, Calib3d.RANSAC, 3);

        Mat obj_corners = new Mat(4, 1, CvType.CV_32FC2);
        Mat scene_corners = new Mat(4, 1, CvType.CV_32FC2);

        obj_corners.put(0, 0, new double[] { 0, 0 });
        obj_corners.put(1, 0, new double[] { objectImage.cols(), 0 });
        obj_corners.put(2, 0, new double[] { objectImage.cols(), objectImage.rows() });
        obj_corners.put(3, 0, new double[] { 0, objectImage.rows() });

        //System.out.println("Transforming object corners to scene corners...");  
        Core.perspectiveTransform(obj_corners, scene_corners, homography);

        Mat img = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR);

        Core.line(img, new Point(scene_corners.get(0, 0)), new Point(scene_corners.get(1, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(1, 0)), new Point(scene_corners.get(2, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(2, 0)), new Point(scene_corners.get(3, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(3, 0)), new Point(scene_corners.get(0, 0)),
                new Scalar(0, 255, 0), 4);

        //java.lang.System.out.println("Dibujando imagen de coincidencias");
        MatOfDMatch goodMatches = new MatOfDMatch();
        goodMatches.fromList(goodMatchesList);

        Features2d.drawMatches(objectImage, objectKeyPoints, sceneImage, sceneKeyPoints, goodMatches,
                matchoutput, matchestColor, newKeypointColor, new MatOfByte(), 2);

        String n_outputImage = "../pre/outputImage_sift.jpg";
        String n_matchoutput = "../pre/matchoutput_sift.jpg";
        String n_img = "../pre/sift.jpg";
        Highgui.imwrite(n_outputImage, outputImage);
        Highgui.imwrite(n_matchoutput, matchoutput);
        Highgui.imwrite(n_img, img);
        java.lang.System.out.println(goodMatches.size().height);
        double result = goodMatches.size().height;//*100/matches.size();
        int score = 0;
        if (result > 26) {
            score = 100;
        } else if (result <= 26 && result > 22) {
            score = 85;
        } else if (result <= 22 && result > 17) {
            score = 50;
        } else if (result <= 17 && result > 11) {
            score = 25;
        } else {
            score = 0;
        }
        java.lang.System.out.println("Score: " + score);
        return score;
    } else {
        java.lang.System.out.println("Objeto no encontrado");
        return 0;
    }
    //System.out.println("Terminando SIFT");  
}

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