Example usage for org.opencv.core Core extractChannel

Introduction

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

Prototype

public static void extractChannel(Mat src, Mat dst, int coi) 

Source Link

Usage

From source file:com.example.colordetector.CamMainActivity.java

License:Apache License

public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
    // The frame currently captured by the camera, converted in the color RGBA
    rgbaFrame = inputFrame.rgba();// ww  w . j av  a2 s  .c o  m

    // Convert the frame in the HSV color space, to be able to identify the color with the thresholds
    Imgproc.cvtColor(rgbaFrame, rgbFrame, Imgproc.COLOR_RGBA2RGB); // Cant't convert directly rgba->hsv
    Imgproc.cvtColor(rgbFrame, hsvFrame, Imgproc.COLOR_RGB2HSV);

    // Create a mask with ONLY zones of the chosen color on the frame currently captured
    Core.inRange(hsvFrame, thresMin, thresMax, inRangeMask);
    filteredFrame.setTo(new Scalar(0, 0, 0));
    rgbFrame.copyTo(filteredFrame, inRangeMask);

    // if the method of shooting image is set to manual, exit and return the filtered image...
    if (!methodAuto) {
        return filteredFrame;
    }

    //...else it was setted the automatic method, so continue with the method
    // Check the H channel of the image to see if the searched color is present on the frame
    Core.extractChannel(filteredFrame, hChannel, 0);

    /* There are two method to verify the color presence; below a little explanation */

    /* checkRange: if almost one pixel of the searched color is found, continue with the countdown
     * Pro -> fast.
     * Versus -> less accurate, possible presence of false positive depending the quality of the camera
     * if(!Core.checkRange(hChannel, true, 0, 1)){ */

    /* Percentage: count the pixel of the searched color, and if there are almost the
     * 0.1% of total pixel of the frame with the searched color, continue with the countdown
     * Pro: more accurate, lower risk of false positive
     * Versus: slower than checkRange
     * N.B.: the threshold percentage is imposted with a low value, otherwise small object will not be seen */

    int perc = Core.countNonZero(hChannel); // Percentage
    if (perc > (frameDim * 0.001)) {
        // if the shooting method is setted to 'immediate', the photo is returned now;
        // otherwise continue with the countdown
        if (!countDown) {
            takePicture();
            return rgbaFrame;
        }

        // 'point' is where the countdown will be visualized; in that case at
        //  a quarter of height and width than left up angle
        Point point = new Point(rgbaFrame.cols() >> 2, rgbaFrame.rows() >> 2);

        // Update the osd countdown every 75*8 ms (if color searched is present)
        // Use the division in 75 ms cause a higher value would give the user the feeling of screen/app 'blocked'.
        if (timeToElapse % 8 == 0) {
            if (osdSecond.compareTo("") == 0)
                osdSecond = ((Integer) (timeToElapse >> 3)).toString();
            else
                osdSecond = osdSecond.concat(".." + (((Integer) (timeToElapse >> 3)).toString()));
            Core.putText(rgbaFrame, osdSecond, point, 1, 3, Scalar.all(255));
        }
        timeToElapse -= 1;

        // the user has framed an object for more than 3 seconds; shoot the photo
        if (timeToElapse <= 0) {
            timeToElapse = 24;
            takePicture();
        }
        // the user has framed an object for less than 3 seconds; wait
        else {
            try {
                synchronized (this) {
                    wait(75);
                }
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
        }
    }
    // the user has NOT framed a color searched object; reset osd
    else {
        timeToElapse = 24;
        osdSecond = "";
    }
    return rgbaFrame;
}

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From source file:de.hftl_projekt.ict.MainActivity.java

/**
 * method to reduce the color (quantize) the given matrix (image)
 * @param image input matrix// w ww.j  a v a2  s .c o  m
 * @return modified input matrix
 */
public Mat reduceColors(Mat image) {
    if (channels.size() == 0) {
        for (int i = 0; i < image.channels(); i++) {
            Mat channel = new Mat(); // fill array with a matrix for each channel
            channels.add(channel);
        }

    }
    int i = 0;
    // process each channel individually
    for (Mat c : channels) {
        Core.extractChannel(image, c, i);
        // binary quantization (set threshold so each color (R, G, B) can have the value (0 or 255) )
        // and using the Otsu algorithm to optimize the quantization
        Imgproc.threshold(c, c, 0, 255, Imgproc.THRESH_BINARY_INV + Imgproc.THRESH_OTSU);
        i++;
    }
    Core.merge(channels, image); // put the channel back together
    return image;
}

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