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

The following examples show how to use org.opencv.core.Core#addWeighted() . These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may want to check out the right sidebar which shows the related API usage.
Example 1
public void sharpenImage() {
        String fileName = "SharpnessExample2.png";
        fileName = "smoothCat.jpg";
        fileName = "blurredText.jpg";
        fileName = "Blurred Text3.jpg";
        try {
//            Not working that well !!!
            Mat source = Imgcodecs.imread(fileName,
                    //                    Imgcodecs.CV_LOAD_IMAGE_COLOR);
                    Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);
            Mat destination = new Mat(source.rows(), source.cols(), source.type());
            Imgproc.GaussianBlur(source, destination, new Size(0, 0), 10);
            // The following was used witht he cat
//            Core.addWeighted(source, 1.5, destination, -0.75, 0, destination);
//            Core.addWeighted(source, 2.5, destination, -1.5, 0, destination);
            Core.addWeighted(source, 1.5, destination, -0.75, 0, destination);
            Imgcodecs.imwrite("sharpenedCat.jpg", destination);
        } catch (Exception ex) {
            ex.printStackTrace();
        }
    }
 
Example 2
Source Project: MOAAP   File: MainActivity.java    License: MIT License 5 votes vote down vote up
void Sobel() {
    Mat grayMat = new Mat();
    Mat sobel = new Mat(); //Mat to store the final result

    //Matrices to store gradient and absolute gradient respectively
    Mat grad_x = new Mat();
    Mat abs_grad_x = new Mat();

    Mat grad_y = new Mat();
    Mat abs_grad_y = new Mat();

    //Converting the image to grayscale
    Imgproc.cvtColor(originalMat, grayMat, Imgproc.COLOR_BGR2GRAY);

    //Calculating gradient in horizontal direction
    Imgproc.Sobel(grayMat, grad_x, CvType.CV_16S, 1, 0, 3, 1, 0);

    //Calculating gradient in vertical direction
    Imgproc.Sobel(grayMat, grad_y, CvType.CV_16S, 0, 1, 3, 1, 0);

    //Calculating absolute value of gradients in both the direction
    Core.convertScaleAbs(grad_x, abs_grad_x);
    Core.convertScaleAbs(grad_y, abs_grad_y);

    //Calculating the resultant gradient
    Core.addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 1, sobel);

    //Converting Mat back to Bitmap
    Utils.matToBitmap(sobel, currentBitmap);
    imageView.setImageBitmap(currentBitmap);
}
 
Example 3
public static Mat sharpenImage(Mat src){
    Mat sharped = new Mat();
    Imgproc.GaussianBlur(src, sharped, new Size(0, 0), 3);
    Core.addWeighted(src, 1.5, sharped, -0.5, 0, sharped);

    return sharped;
}
 
Example 4
Source Project: Camdroid   File: UnsharpenMaskProcessor.java    License: Apache License 2.0 5 votes vote down vote up
protected void execute() {
    out = this.rgb();

    Imgproc.blur(out, this.mask, new Size(sigma_x, sigma_x));
    Core.addWeighted(out, (double) alpha / 10, this.mask,
            ((double) beta - 10) / 10, 0, out);
}
 
Example 5
Source Project: OpenTLDAndroid   File: PatchGenerator.java    License: Apache License 2.0 5 votes vote down vote up
/**
	 * 
	 * @param image
	 * @param T
	 * @param patch OUTPUT
	 * @param patchSize
	 */
	void generate(final Mat image, final Mat T, Mat patch, Size patchSize, final RNG rng){
	    patch.create( patchSize, image.type() );
	    if( backgroundMin != backgroundMax ) {
	    	Core.randu(patch, backgroundMin, backgroundMax);
	    	// TODO if that null scalar OK or should it be new Scalar(0) ?
	    	Imgproc.warpAffine(image, patch, T, patchSize, Imgproc.INTER_LINEAR, Imgproc.BORDER_TRANSPARENT, null);
	    } else {
	    	Imgproc.warpAffine(image, patch, T, patchSize, Imgproc.INTER_LINEAR, Imgproc.BORDER_CONSTANT, new Scalar(backgroundMin));
	    }

	    int ksize = randomBlur ? rng.nextInt() % 9 - 5 : 0;
	    if( ksize > 0 ) {
	        ksize = ksize * 2 + 1;
	        Imgproc.GaussianBlur(patch, patch, new Size(ksize, ksize), 0, 0);
	    }

	    if( noiseRange > 0 ) {
	        final Mat noise = new Mat(patchSize, image.type());
	        int delta = (image.depth() == CvType.CV_8U ? 128 : (image.depth() == CvType.CV_16U ? 32768 : 0));
	        Core.randn(noise, delta, noiseRange);
	        
	        // TODO this was different !!
	        Core.addWeighted(patch, 1, noise, 1, -delta, patch);
	        
//	        if( backgroundMin != backgroundMax )
//	            addWeighted(patch, 1, noise, 1, -delta, patch);
//	        else
//	        {
//	            for( int i = 0; i < patchSize.height; i++ )
//	            {
//	                uchar* prow = patch.ptr<uchar>(i);
//	                const uchar* nrow =  noise.ptr<uchar>(i);
//	                for( int j = 0; j < patchSize.width; j++ )
//	                    if( prow[j] != backgroundMin )
//	                        prow[j] = saturate_cast<uchar>(prow[j] + nrow[j] - delta);
//	            }
//	        }
	    }		
	}
 
Example 6
public static Rect detectBorder(Mat original){
    Mat src = original.clone();
    Log.d(TAG, "1 original: " + src.toString());

    Imgproc.GaussianBlur(src, src, new Size(3, 3), 0);
    Log.d(TAG, "2.1 --> Gaussian blur done\n blur: " + src.toString());

    Imgproc.cvtColor(src, src, Imgproc.COLOR_RGBA2GRAY);
    Log.d(TAG, "2.2 --> Grayscaling done\n gray: " + src.toString());

    Mat sobelX = new Mat();
    Mat sobelY = new Mat();

    Imgproc.Sobel(src, sobelX, CvType.CV_32FC1, 2, 0, 5, 1, 0);
    Log.d(TAG, "3.1 --> Sobel done.\n X: " + sobelX.toString());
    Imgproc.Sobel(src, sobelY, CvType.CV_32FC1, 0, 2, 5, 1, 0);
    Log.d(TAG, "3.2 --> Sobel done.\n Y: " + sobelY.toString());

    Mat sum_img = new Mat();
    Core.addWeighted(sobelX, 0.5, sobelY, 0.5, 0.5, sum_img);
    //Core.add(sobelX, sobelY, sum_img);
    Log.d(TAG, "4 --> Addition done. sum: " + sum_img.toString());

    sobelX.release();
    sobelY.release();

    Mat gray = new Mat();
    Core.normalize(sum_img, gray, 0, 255, Core.NORM_MINMAX, CvType.CV_8UC1);
    Log.d(TAG, "5 --> Normalization done. gray: " + gray.toString());
    sum_img.release();

    Mat row_proj = new Mat();
    Mat col_proj = new Mat();
    Core.reduce(gray, row_proj, 1, Core.REDUCE_AVG, CvType.CV_8UC1);
    Log.d(TAG, "6.1 --> Reduce done. row: " + row_proj.toString());

    Core.reduce(gray, col_proj, 0, Core.REDUCE_AVG, CvType.CV_8UC1);
    Log.d(TAG, "6.2 --> Reduce done. col: " + col_proj.toString());
    gray.release();

    Imgproc.Sobel(row_proj, row_proj, CvType.CV_8UC1, 0, 2);
    Log.d(TAG, "7.1 --> Sobel done. row: " + row_proj.toString());

    Imgproc.Sobel(col_proj, col_proj, CvType.CV_8UC1, 2, 0);
    Log.d(TAG, "7.2 --> Sobel done. col: " + col_proj.toString());

    Rect result = new Rect();

    int half_pos = (int) (row_proj.total()/2);
    Mat row_sub = new Mat(row_proj, new Range(0, half_pos), new Range(0, 1));
    Log.d(TAG, "8.1 --> Copy sub matrix done. row: " + row_sub.toString());
    result.y = (int) Core.minMaxLoc(row_sub).maxLoc.y;
    Log.d(TAG, "8.2 --> Minmax done. Y: " + result.y);
    row_sub.release();
    Mat row_sub2 = new Mat(row_proj, new Range(half_pos, (int) row_proj.total()), new Range(0, 1));
    Log.d(TAG, "8.3 --> Copy sub matrix done. row: " + row_sub2.toString());
    result.height = (int) (Core.minMaxLoc(row_sub2).maxLoc.y + half_pos - result.y);
    Log.d(TAG, "8.4 --> Minmax done. Height: " + result.height);
    row_sub2.release();

    half_pos = (int) (col_proj.total()/2);
    Mat col_sub = new Mat(col_proj, new Range(0, 1), new Range(0, half_pos));
    Log.d(TAG, "9.1 --> Copy sub matrix done. col: " + col_sub.toString());
    result.x = (int) Core.minMaxLoc(col_sub).maxLoc.x;
    Log.d(TAG, "9.2 --> Minmax done. X: " + result.x);
    col_sub.release();
    Mat col_sub2 = new Mat(col_proj, new Range(0, 1), new Range(half_pos, (int) col_proj.total()));
    Log.d(TAG, "9.3 --> Copy sub matrix done. col: " + col_sub2.toString());
    result.width = (int) (Core.minMaxLoc(col_sub2).maxLoc.x + half_pos - result.x);
    Log.d(TAG, "9.4 --> Minmax done. Width: " + result.width);
    col_sub2.release();

    row_proj.release();
    col_proj.release();
    src.release();

    return result;
}