Example usage for org.opencv.imgproc Imgproc dilate

List of usage examples for org.opencv.imgproc Imgproc dilate

Introduction

In this page you can find the example usage for org.opencv.imgproc Imgproc dilate.

Prototype

public static void dilate(Mat src, Mat dst, Mat kernel, Point anchor, int iterations) 

Source Link

Usage

From source file:classes.FloodFiller.java

private void fillFrom(Point seed, int lo, int up, Scalar backgroundColor, Scalar contourFillingColor) {

    Mat object = ObjectGenerator.extract(image, seed.x, seed.y, 10, 10);
    this.meanColor = Core.mean(object);

    Rect ccomp = new Rect();
    Mat mask = Mat.zeros(image.rows() + 2, image.cols() + 2, CvType.CV_8UC1);

    int connectivity = 4;
    int newMaskVal = 255;
    int ffillMode = 1;

    int flags = connectivity + (newMaskVal << 8) + (ffillMode == 1 ? Imgproc.FLOODFILL_FIXED_RANGE : 0);

    Scalar newVal = new Scalar(0.299, 0.587, 0.114);

    Imgproc.threshold(mask, mask, 1, 128, Imgproc.THRESH_BINARY);

    filledArea = Imgproc.floodFill(image.clone(), mask, seed, newVal, ccomp, new Scalar(lo, lo, lo),
            new Scalar(up, up, up), flags);

    //        Highgui.imwrite("mask.png", mask);
    ImageUtils.saveImage(mask, "mask.png", request);

    morphologicalImage = new Mat(image.size(), CvType.CV_8UC3);

    Mat element = new Mat(3, 3, CvType.CV_8U, new Scalar(1));

    ArrayList<Mat> mask3 = new ArrayList<Mat>();
    mask3.add(mask);/* www.  ja  v  a2 s  .  c  o  m*/
    mask3.add(mask);
    mask3.add(mask);
    Core.merge(mask3, mask);

    // Applying morphological filters
    Imgproc.erode(mask, morphologicalImage, element);
    Imgproc.morphologyEx(morphologicalImage, morphologicalImage, Imgproc.MORPH_CLOSE, element,
            new Point(-1, -1), 9);
    Imgproc.morphologyEx(morphologicalImage, morphologicalImage, Imgproc.MORPH_OPEN, element, new Point(-1, -1),
            2);
    Imgproc.resize(morphologicalImage, morphologicalImage, image.size());

    //        Highgui.imwrite("morphologicalImage.png", morphologicalImage);
    ImageUtils.saveImage(morphologicalImage, "morphologicalImage.png", request);

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

    Core.split(mask, mask3);
    Mat binarymorphologicalImage = mask3.get(0);

    Imgproc.findContours(binarymorphologicalImage.clone(), contours, new Mat(), Imgproc.RETR_EXTERNAL,
            Imgproc.CHAIN_APPROX_NONE);

    contoursImage = new Mat(image.size(), CvType.CV_8UC3, backgroundColor);

    int thickness = -1; // Thicknes should be lower than zero in order to drawn the filled contours
    Imgproc.drawContours(contoursImage, contours, -1, contourFillingColor, thickness); // Drawing all the contours found
    //        Highgui.imwrite("allContoursImage.png", contoursImage);
    ImageUtils.saveImage(contoursImage, "allContoursImage.png", request);

    if (contours.size() > 1) {

        int minContourWith = 20;
        int minContourHeight = 20;
        int maxContourWith = 6400 / 2;
        int maxContourHeight = 4800 / 2;

        contours = filterContours(contours, minContourWith, minContourHeight, maxContourWith, maxContourHeight);
    }

    if (contours.size() > 0) {

        MatOfPoint biggestContour = contours.get(0); // getting the biggest contour
        contourArea = Imgproc.contourArea(biggestContour);

        if (contours.size() > 1) {
            biggestContour = Collections.max(contours, new ContourComparator()); // getting the biggest contour in case there are more than one
        }

        Point[] points = biggestContour.toArray();
        path = "M " + (int) points[0].x + " " + (int) points[0].y + " ";
        for (int i = 1; i < points.length; ++i) {
            Point v = points[i];
            path += "L " + (int) v.x + " " + (int) v.y + " ";
        }
        path += "Z";

        biggestContourImage = new Mat(image.size(), CvType.CV_8UC3, backgroundColor);

        Imgproc.drawContours(biggestContourImage, contours, 0, contourFillingColor, thickness);

        //            Highgui.imwrite("biggestContourImage.png", biggestContourImage);
        ImageUtils.saveImage(biggestContourImage, "biggestContourImage.png", request);

        Mat maskForColorExtraction = biggestContourImage.clone();

        if (isWhite(backgroundColor)) {
            Imgproc.dilate(maskForColorExtraction, maskForColorExtraction, new Mat(), new Point(-1, -1), 3);
        } else {
            Imgproc.erode(maskForColorExtraction, maskForColorExtraction, new Mat(), new Point(-1, -1), 3);
        }

        //            Highgui.imwrite("maskForColorExtraction.png", maskForColorExtraction);
        ImageUtils.saveImage(maskForColorExtraction, "maskForColorExtraction.png", request);

        Mat extractedColor = new Mat();

        if (isBlack(backgroundColor) && isWhite(contourFillingColor)) {
            Core.bitwise_and(maskForColorExtraction, image, extractedColor);

        } else {
            Core.bitwise_or(maskForColorExtraction, image, extractedColor);
        }

        //            Highgui.imwrite("extractedColor.png", extractedColor);
        ImageUtils.saveImage(extractedColor, "extractedColor.png", request);

        computedSearchWindow = Imgproc.boundingRect(biggestContour);
        topLeftCorner = computedSearchWindow.tl();

        Rect croppingRect = new Rect(computedSearchWindow.x, computedSearchWindow.y,
                computedSearchWindow.width - 1, computedSearchWindow.height - 1);

        Mat imageForTextRecognition = new Mat(extractedColor.clone(), croppingRect);
        //            Highgui.imwrite(outImageName, imageForTextRecognition);
        ImageUtils.saveImage(imageForTextRecognition, outImageName, request);

        //            
        //
        //            Mat data = new Mat(imageForTextRecognition.size(), CvType.CV_8UC3, backgroundColor);
        //            imageForTextRecognition.copyTo(data);
        //            data.convertTo(data, CvType.CV_8UC3);
        //
        //            // The meanColor variable represents the color in the GBR space, the following line transforms this to the RGB color space, which
        //            // is assumed in the prepareImage method of the TextRecognitionPreparer class
        //            Scalar userColor = new Scalar(meanColor.val[2], meanColor.val[1], meanColor.val[0]);
        //
        //            ArrayList<String> recognizableImageNames = TextRecognitionPreparer.generateRecognizableImagesNames(data, backgroundColor, userColor);
        //            for (String imageName : recognizableImageNames) {
        //
        //                try {
        //                    // First recognition step
        //                    String recognizedText = TextRecognizer.recognize(imageName, true).trim();
        //                    if (recognizedText != null && !recognizedText.isEmpty()) {
        //                        recognizedStrings.add(recognizedText);
        //                    }
        //                    // Second recognition step
        //                    recognizedText = TextRecognizer.recognize(imageName, false).trim();
        //                    if (recognizedText != null && !recognizedText.isEmpty()) {
        //                        recognizedStrings.add(recognizedText);
        //                    }
        //                    
        //                } catch (Exception e) {
        //                }
        //            }
        //            
        ////            ArrayList<BufferedImage> recognizableBufferedImages = TextRecognitionPreparer.generateRecognizableBufferedImages(data, backgroundColor, userColor);
        ////            for (BufferedImage bufferedImage : recognizableBufferedImages) {
        ////                try {
        ////                    // First recognition step
        ////                    String recognizedText = TextRecognizer.recognize(bufferedImage, true).trim();
        ////                    if (recognizedText != null && !recognizedText.isEmpty()) {
        ////                        recognizedStrings.add(recognizedText);
        ////                    }
        ////                    // Second recognition step
        ////                    recognizedText = TextRecognizer.recognize(bufferedImage, false).trim();
        ////                    if (recognizedText != null && !recognizedText.isEmpty()) {
        ////                        recognizedStrings.add(recognizedText);
        ////                    }
        ////                    
        ////                } catch (Exception e) {
        ////                }
        ////            }
        //
        //            
        //            

        // compute all moments
        Moments mom = Imgproc.moments(biggestContour);
        massCenter = new Point(mom.get_m10() / mom.get_m00(), mom.get_m01() / mom.get_m00());

        // draw black dot
        Core.circle(contoursImage, massCenter, 4, contourFillingColor, 8);
    }

}

From source file:fuzzycv.MainFrame.java

private Mat removeBG(Mat frame) {

    Mat hsvImg = new Mat();
    List<Mat> hsvPlanes = new ArrayList<>();
    Mat thresholdImg = new Mat();

    //threshold the image with the histogram average value
    hsvImg.create(frame.size(), CvType.CV_8U);
    Imgproc.cvtColor(frame, hsvImg, Imgproc.COLOR_BGR2HSV);
    Core.split(hsvImg, hsvPlanes);/*from   w  w  w  .  j  av  a 2 s.c  om*/

    double threshValue = getHistoAvg(hsvImg, hsvPlanes.get(0));

    if (inverseCheckBox.isSelected()) {
        Imgproc.threshold(hsvPlanes.get(0), thresholdImg, threshValue, 179.0, Imgproc.THRESH_BINARY_INV);
    } else {
        Imgproc.threshold(hsvPlanes.get(0), thresholdImg, threshValue, 179.0, Imgproc.THRESH_BINARY);
    }

    Imgproc.blur(thresholdImg, thresholdImg, new Size(5, 5));

    // dilate to fill gaps, erode to smooth edges
    Imgproc.dilate(thresholdImg, thresholdImg, new Mat(), new Point(-1, 1), 6);
    Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, 1), 6);

    Imgproc.threshold(thresholdImg, thresholdImg, threshValue, 179.0, Imgproc.THRESH_BINARY);

    // create the new image
    Mat foreground = new Mat(frame.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
    frame.copyTo(foreground, thresholdImg);

    return foreground;
}

From source file:javafx1.JavaFX1.java

private Mat doBackgroundRemoval(Mat frame) {
        // init/*from w w  w.ja va  2 s  .c  o m*/
        Mat hsvImg = new Mat();
        List<Mat> hsvPlanes = new ArrayList<>();
        Mat thresholdImg = new Mat();

        int thresh_type = Imgproc.THRESH_BINARY_INV;
        //inverse
        thresh_type = Imgproc.THRESH_BINARY;

        // threshold the image with the average hue value
        hsvImg.create(frame.size(), CvType.CV_8U);
        Imgproc.cvtColor(frame, hsvImg, Imgproc.COLOR_BGR2HSV);
        Core.split(hsvImg, hsvPlanes);

        // get the average hue value of the image
        double threshValue = this.getHistAverage(hsvImg, hsvPlanes.get(0));

        Imgproc.threshold(hsvPlanes.get(0), thresholdImg, threshValue, 179.0, thresh_type);

        Imgproc.blur(thresholdImg, thresholdImg, new Size(5, 5));

        // dilate to fill gaps, erode to smooth edges
        Imgproc.dilate(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 1);
        Imgproc.erode(thresholdImg, thresholdImg, new Mat(), new Point(-1, -1), 3);

        Imgproc.threshold(thresholdImg, thresholdImg, threshValue, 179.0, Imgproc.THRESH_BINARY);

        // create the new image
        Mat foreground = new Mat(frame.size(), CvType.CV_8UC3, new Scalar(255, 255, 255));
        frame.copyTo(foreground, thresholdImg);

        return foreground;
    }