Java Code Examples for org.opencv.core.Core#bitwise_or()

Mat buildSkeleton(Mat img){
    Mat morph = Imgproc.getStructuringElement(Imgproc.CV_SHAPE_CROSS, new Size(3, 3));
    Mat skel = new Mat(img.size(), CvType.CV_8UC1, Scalar.all(0));
    Mat eroded = new Mat();
    Mat temp = new Mat();

    boolean done = false;

    do{
        Imgproc.morphologyEx(img, eroded, Imgproc.MORPH_ERODE, morph);
        Imgproc.morphologyEx(eroded, temp, Imgproc.MORPH_DILATE, morph);
        Core.subtract(img, temp, temp);
        Core.bitwise_or(skel, temp, skel);
        eroded.copyTo(img);

        done = Core.countNonZero(img) == 0;
    }while (!done);

    return skel;
}
 

/**
 * Process an rgba image. The results can be drawn on retrieved later.
 * This method does not modify the image.
 *
 * @param rgbaImage An RGBA image matrix
 */
public void process(Mat rgbaImage) {
    Imgproc.pyrDown(rgbaImage, mPyrDownMat);
    Imgproc.pyrDown(mPyrDownMat, mPyrDownMat);

    Imgproc.cvtColor(mPyrDownMat, mHsvMat, Imgproc.COLOR_RGB2HSV_FULL);

    //Test whether we need two inRange operations (only if the hue crosses over 255)
    if (upperBound.getScalar().val[0] <= 255) {
        Core.inRange(mHsvMat, lowerBound.getScalar(), upperBound.getScalar(), mMask);
    } else {
        //We need two operations - we're going to OR the masks together
        Scalar lower = lowerBound.getScalar().clone();
        Scalar upper = upperBound.getScalar().clone();
        while (upper.val[0] > 255)
            upper.val[0] -= 255;
        double tmp = lower.val[0];
        lower.val[0] = 0;
        //Mask 1 - from 0 to n
        Core.inRange(mHsvMat, lower, upper, mMaskOne);
        //Mask 2 - from 255-n to 255
        lower.val[0] = tmp;
        upper.val[0] = 255;

        Core.inRange(mHsvMat, lower, upper, mMask);
        //OR the two masks
        Core.bitwise_or(mMaskOne, mMask, mMask);
    }

    //Dilate (blur) the mask to decrease processing power
    Imgproc.dilate(mMask, mDilatedMask, new Mat());

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

    Imgproc.findContours(mDilatedMask, contourListTemp, mHierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);

    // Filter contours by area and resize to fit the original image size
    contours.clear();
    for (MatOfPoint c : contourListTemp) {
        Core.multiply(c, new Scalar(4, 4), c);
        contours.add(new Contour(c));
    }
}
 

private void findLocations(Mat searchMat)
{
    _locationValues.clear();
    SparseIntArray areas = new SparseIntArray(4);

    for(int i = 0; i < NUM_CODES; i++)
    {
        Mat mask = new Mat();
        List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
        Mat hierarchy = new Mat();

        if(i == 2)
        {
            // combine the two ranges for red
            Core.inRange(searchMat, LOWER_RED1, UPPER_RED1, mask);
            Mat rmask2 = new Mat();
            Core.inRange(searchMat, LOWER_RED2, UPPER_RED2, rmask2);
            Core.bitwise_or(mask, rmask2, mask);
        }
        else
            Core.inRange(searchMat, COLOR_BOUNDS[i][0], COLOR_BOUNDS[i][1], mask);

        Imgproc.findContours(mask, contours, hierarchy, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE);
        for (int contIdx = 0; contIdx < contours.size(); contIdx++)
        {
            int area;
            if ((area = (int)Imgproc.contourArea(contours.get(contIdx))) > 20)
            {
                Moments M = Imgproc.moments(contours.get(contIdx));
                int cx = (int) (M.get_m10() / M.get_m00());

                // if a colour band is split into multiple contours
                // we take the largest and consider only its centroid
                boolean shouldStoreLocation = true;
                for(int locIdx = 0; locIdx < _locationValues.size(); locIdx++)
                {
                    if(Math.abs(_locationValues.keyAt(locIdx) - cx) < 10)
                    {
                        if (areas.get(_locationValues.keyAt(locIdx)) > area)
                        {
                            shouldStoreLocation = false;
                            break;
                        }
                        else
                        {
                            _locationValues.delete(_locationValues.keyAt(locIdx));
                            areas.delete(_locationValues.keyAt(locIdx));
                        }
                    }
                }

                if(shouldStoreLocation)
                {
                    areas.put(cx, area);
                    _locationValues.put(cx, i);
                }
            }
        }
    }
}