Example usage for org.opencv.core Mat Mat

Introduction

In this page you can find the example usage for org.opencv.core Mat Mat.

Prototype

public Mat() 

Source Link

Usage

From source file:imageanalysis.Analyzer.java

private Mat findDifferences() {
    Mat image = ImgTools.getImageFromClipboard();

    // Gets images (both halves)
    Mat leftHalf = image.submat(left);// w  w w  . jav a  2  s. com
    Mat rightHalf = image.submat(right);

    // Computes their difference
    Mat diff1 = new Mat();
    Mat diff2 = new Mat();
    Core.subtract(leftHalf, rightHalf, diff1);
    Core.subtract(rightHalf, leftHalf, diff2);

    // Gets sum of both differences (image that highlightes different objects)
    Mat sum = new Mat(diff1.size(), CvType.CV_32F);
    Core.add(diff1, diff2, sum);
    // Normalize
    Core.normalize(sum, sum, 0, 255, Core.NORM_MINMAX);
    sum.convertTo(sum, CvType.CV_8U);

    return sum;

}

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From source file:imageanalysis.Analyzer.java

public boolean compareRoiAgainstPattern(int xcoord, int ycoord, int width, int height) {
    screen = ImgTools.getImageFromClipboard();

    // Crops roi around chosen mouse point
    Rect roi = new Rect(xcoord - width / 2, ycoord - height / 2, width, height);
    Mat actionButton = screen.submat(roi);

    // Preprocessing
    Imgproc.cvtColor(actionButton, actionButton, Imgproc.COLOR_BGR2GRAY);
    //        Imgproc.medianBlur(actionButton, actionButton, 5);

    // Referent pattern
    Mat bonefoodPattern = Patterns.getBonefoodPattern();
    //        Imgproc.medianBlur(bonefoodPattern, bonefoodPattern, 5);

    // Match template
    // ... result should be the refPoint
    Mat result = new Mat();
    Imgproc.matchTemplate(actionButton, bonefoodPattern, result, Imgproc.TM_SQDIFF);
    Point p = Core.minMaxLoc(result).minLoc;
    //        System.out.println(p.toString());

    return p.equals(refPoint);
}

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From source file:imageanalysis.Analyzer.java

public Point checkForX() {
    screen = ImgTools.getImageFromClipboard();

    Mat image = screen.clone();//from   w  w  w  . j  a  va 2  s  .c  o m

    // Preprocessing
    Imgproc.cvtColor(image, image, Imgproc.COLOR_BGR2GRAY);

    // Referent pattern
    Mat xPattern = Patterns.getXbuttPattern();

    // Match template
    // ... result should be the refPoint
    Mat result = new Mat();
    Imgproc.matchTemplate(image, xPattern, result, Imgproc.TM_SQDIFF);

    Core.MinMaxLocResult mm = Core.minMaxLoc(result);

    Point p = mm.minLoc;
    double val = mm.minVal;

    if (val < 1000000) {
        p.x += 10;
        p.y += 10;
        return p;
    } else {
        return null;
    }
}

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From source file:imageanalyzercv.ImageAnalyzerCV.java

/**
 * @param args the command line arguments
 *//*from   www  . j  a va 2s  .com*/
public static void main(String[] args) {
    System.out.println("path: " + System.getProperty("java.library.path"));
    System.loadLibrary("opencv_java300");

    Mat m = Highgui.imread("/Users/chintan/Downloads/software/image_analyis/mydata/SAM_0763.JPG");
    System.out.println("m = " + m.height());
    MatOfKeyPoint points = new MatOfKeyPoint();
    FeatureDetector.create(FeatureDetector.SURF).detect(m, points);

    Mat m2 = Highgui.imread("/Users/chintan/Downloads/software/image_analyis/mydata/SAM_0764.JPG");
    System.out.println("m = " + m2.height());
    MatOfKeyPoint points2 = new MatOfKeyPoint();
    FeatureDetector.create(FeatureDetector.SURF).detect(m2, points2);

    DescriptorExtractor SurfExtractor = DescriptorExtractor.create(DescriptorExtractor.BRISK);
    Mat imag1Desc = new Mat();
    SurfExtractor.compute(m, points, imag1Desc);

    Mat imag2Desc = new Mat();
    SurfExtractor.compute(m2, points2, imag2Desc);

    MatOfDMatch matches = new MatOfDMatch();

    Mat imgd = new Mat();
    imag1Desc.copyTo(imgd);
    System.out.println(imgd.size());
    DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING).match(imag2Desc, imag1Desc,
            (MatOfDMatch) matches);

    double min_distance = 1000.0;
    double max_distance = 0.0;
    DMatch[] matchArr = matches.toArray();
    for (int i = 0; i < matchArr.length; i++) {
        if (matchArr[i].distance > max_distance)
            max_distance = matchArr[i].distance;
        if (matchArr[i].distance < min_distance)
            min_distance = matchArr[i].distance;
    }

    ArrayList<DMatch> good_matches = new ArrayList<DMatch>();

    System.out.println("Min Distance: " + min_distance + "  Max distance: " + max_distance);
    double totalScore = 0.0;
    for (int j = 0; j < imag1Desc.rows() && j < matchArr.length; j++) {
        if ((matchArr[j].distance <= (11 * min_distance)) && (matchArr[j].distance >= min_distance * 1)) {
            good_matches.add(matchArr[j]);
            //System.out.println(matchArr[j]);
            totalScore = totalScore + matchArr[j].distance;

        }
        //good_matches.add(matchArr[j]);

    }
    System.out.println((1 - (totalScore / (good_matches.size() * ((max_distance + min_distance) / 2)))) * 100);
    // System.out.println(matches.toList().size());
    Mat out = new Mat();
    MatOfDMatch mats = new MatOfDMatch();
    mats.fromList(good_matches);
    Features2d.drawMatches(m2, points2, m, points, mats, out);
    Highgui.imwrite("/Users/chintan/Downloads/one2.jpg", out);
}

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From source file:imagegame.Camera.java

public Camera() {
    super("Camera - click screen to take a picture");
    initComponents();//from  ww w.  ja  va  2s. co m

    setLayout(new BorderLayout());
    setLibraryPath();
    System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
    videoCapture = new VideoCapture();
    videoCapture.open(0);

    System.out.println("Camera open: " + videoCapture.isOpened());
    if (videoCapture.isOpened()) {
        this.addWindowListener(new WindowAdapter() {
            @Override
            public void windowClosing(WindowEvent e) {
                // Implementation here

                stop();
                System.out.println("Camera released");

            }
        });//end WindowListener
        JPanel cameraJPanel = new JPanel() {
            @Override
            public void paint(Graphics g) {
                g.drawImage(image, 0, 0, this);
            }
        };
        cameraJPanel.setPreferredSize(new Dimension(420, 500));
        add(cameraJPanel, BorderLayout.NORTH);

        Runnable frameGrabber;
        frameGrabber = () -> {
            Mat mat = new Mat();
            videoCapture.read(mat);

            image = mat2BufferedImage(mat);
            //g.drawImage(image, 0, 0,this);
            cameraJPanel.repaint();
            //              rectList.stream().forEach((Rectangle2D rect) -> {
            //                g2d.strokeRect(rect.getMinX(), rect.getMinY(), rect.getWidth(), rect.getHeight());
            //            });
        }; //end frameGrabber
        this.timer = Executors.newSingleThreadScheduledExecutor();
        this.timer.scheduleAtFixedRate(frameGrabber, 0, 133, TimeUnit.MILLISECONDS);
    } else {//if videoCapture.isOpen() is false
        JOptionPane.showMessageDialog(null, "You have no camera installed");
    }
}

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From source file:imageprocess.HistogramProcessor.java

public static Mat getGrayHistogram(Mat image) {

    Mat grayHist = new Mat();

    // Compute histogram
    Imgproc.calcHist(Arrays.asList(image), //histogram of 1 image only
            new MatOfInt(0), // the channel used
            new Mat(), // no mask is used
            grayHist, // the resulting histogram
            new MatOfInt(256), // number of bins, hist size
            new MatOfFloat(0.0f, 255.0f) // BRG range
    );//ww w  . j  a v a  2 s  . c  om

    return grayHist;
}

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From source file:imageprocess.HistogramProcessor.java

public static Mat getHistogram(Mat image) {

    Mat hist = new Mat();

    // Compute histogram
    Imgproc.calcHist(Arrays.asList(image), //histogram of 1 image only
            new MatOfInt(0, 1, 2), // the channel used
            new Mat(), // no mask is used
            hist, // the resulting histogram
            new MatOfInt(256, 256, 256), // number of bins, hist size
            new MatOfFloat(0.0f, 255.0f, 0.0f, 255.0f, 0.0f, 255.0f) // BRG range
    );/*from   www  .  jav  a  2s.  c  o m*/

    return hist;
}

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From source file:imageprocess.HistogramProcessor.java

public static Mat getHueHistogram(Mat image) {

    Mat hue = new Mat();

    // Compute histogram
    Imgproc.calcHist(Arrays.asList(image), //histogram of 1 image only
            new MatOfInt(0, 1, 2), // the channel used
            new Mat(), // no mask is used
            hue, // the resulting histogram
            new MatOfInt(256, 256, 256), // number of bins, hist size
            new MatOfFloat(0.0f, 255.0f, 0.0f, 255.0f, 0.0f, 255.0f) // BRG range
    );/*from  w ww .  j a v  a 2 s.c o  m*/

    return hue;
}

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From source file:imageprocess.ObjectFinder.java

public Mat getHueHistogram(final Mat image, int minSaturation) {

    Mat hist = new Mat();

    // Convert to Lab color space
    Mat hsv = new Mat();
    Imgproc.cvtColor(image, hsv, CV_BGR2HSV);
    Mat mask = new Mat();
    if (minSaturation > 0) {
        // Spliting the 3 channels into 3 images
        List<Mat> v = new ArrayList<>();
        Core.split(hsv, v);//from w ww . ja v  a 2 s  . c  o m
        // Mask out the low saturated pixels
        Imgproc.threshold(v.get(1), mask, minSaturation, 255, THRESH_BINARY);
    }
    // Compute histogram
    Imgproc.calcHist(Arrays.asList(image), new MatOfInt(0), // the hue channel used
            mask, // no mask is used
            hist, // the resulting histogram
            new MatOfInt(256), // number of bins
            new MatOfFloat(0.0f, 180.0f) // pixel value range
    );

    return hist;
}

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From source file:imageprocess.ObjectFinder.java

public Mat find(final Mat image, MatOfInt channels, MatOfFloat ranges) {

    Mat result = new Mat();

    if (isIsSparse()) { // call the right function based on histogram type

        Imgproc.calcBackProject(Arrays.asList(image), channels, // vector specifying what histogram dimensions belong to what image channels
                ROIHistogram, // the histogram we are using
                result, // the resulting back projection image
                ranges, // the range of values, for each dimension
                255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
        );//w  w  w .ja v  a 2s.  c  om

    } else {
        Imgproc.calcBackProject(Arrays.asList(image), channels, // vector specifying what histogram dimensions belong to what image channels
                ROIHistogram, // the histogram we are using
                result, // the resulting back projection image
                ranges, // the range of values, for each dimension
                255.0 // the scaling factor is chosen such that a histogram value of 1 maps to 255
        );
    }

    // Threshold back projection to obtain a binary image
    Mat thresholded = new Mat(result.rows(), result.cols(), result.type());
    if (getThreshold() > 0.0) {
        Imgproc.threshold(result, thresholded, 255 * getThreshold(), 255, THRESH_BINARY);
    }

    return thresholded;
}

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