List of usage examples for org.opencv.core Core split
public static void split(Mat m, List<Mat> mv)
From source file:Retrive.java
public Mat query_histo(Mat query_img) { Vector<Mat> bgr_planes = new Vector<>(); Core.split(query_img, bgr_planes); MatOfInt histSize = new MatOfInt(256); final MatOfFloat histRange = new MatOfFloat(0f, 256f); //boolean accumulate = false; Mat q_hist = new Mat(); int hist_w = 512; int hist_h = 600; long bin_w;/* w w w . j a v a2 s. c om*/ bin_w = Math.round((double) (hist_w / 256)); Mat histImage = new Mat(hist_h, hist_w, CvType.CV_8UC3); Imgproc.calcHist(bgr_planes, new MatOfInt(0), new Mat(), q_hist, histSize, histRange); Core.normalize(q_hist, q_hist, 0, histImage.rows(), Core.NORM_MINMAX, -1, new Mat()); return q_hist; }
From source file:Retrive.java
public Mat histo(Mat imgs) { Vector<Mat> bgr_planes = new Vector<>(); Core.split(imgs, bgr_planes); MatOfInt histSize = new MatOfInt(256); final MatOfFloat histRange = new MatOfFloat(0f, 256f); boolean accumulate = false; Mat b_hist = new Mat(); int hist_w = 512; int hist_h = 600; //long bin_w; //bin_w = Math.round((double) (hist_w / 256)); Mat histImage = new Mat(hist_h, hist_w, CvType.CV_8UC3); Imgproc.calcHist(bgr_planes, new MatOfInt(0), new Mat(), b_hist, histSize, histRange, accumulate); Core.normalize(b_hist, b_hist, 0, histImage.rows(), Core.NORM_MINMAX, -1, new Mat()); return b_hist; }
From source file:airhockeyjava.detection.PS3EyeFrameGrabber.java
License:Open Source License
/** * Grab one frame; the caller have to make a copy of returned image before * processing./* www. jav a 2s.c o m*/ * * It will throw null pointer exception if not started before grabbing. * * @return "read-only" RGB, 3-channel */ public Mat grabMat() { Mat matImg = new Mat(this.imageHeight, this.imageWidth, CvType.CV_8UC4); int[] img = grab_RGB4(); ByteBuffer byteBuffer = ByteBuffer.allocate(img.length * 4); IntBuffer intBuffer = byteBuffer.asIntBuffer(); intBuffer.put(img); byte[] array = byteBuffer.array(); matImg.put(0, 0, array); List<Mat> mv = new ArrayList<Mat>(); Core.split(matImg, mv); mv.remove(0); Core.merge(mv, matImg); return matImg; }
From source file:Clases.Segmentador.java
public Mat descompCanImg(Mat grayscale, int canal) { List<Mat> rgb = new ArrayList<Mat>(3); Core.split(grayscale, rgb); return rgb.get(canal); }
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);//from w ww. java 2 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:classes.TextRecognitionPreparer.java
public static Mat equalizeIntensity(Mat inputImage) { if (inputImage.channels() >= 3) { Mat ycrcb = new Mat(); Imgproc.cvtColor(inputImage, ycrcb, Imgproc.COLOR_BGR2YUV); ArrayList<Mat> channels = new ArrayList<Mat>(); Core.split(ycrcb, channels); Mat equalized = new Mat(); Imgproc.equalizeHist(channels.get(0), equalized); channels.set(0, equalized);// w w w .ja v a 2 s . c om Core.merge(channels, ycrcb); Mat result = new Mat(); Imgproc.cvtColor(ycrcb, result, Imgproc.COLOR_YUV2BGR); return result; } return null; }
From source file:com.shootoff.camera.Camera.java
License:Open Source License
public static Mat colorTransfer(Mat source, Mat target) { Mat src = new Mat(); Mat dst = new Mat(); Imgproc.cvtColor(source, src, Imgproc.COLOR_BGR2Lab); Imgproc.cvtColor(target, dst, Imgproc.COLOR_BGR2Lab); ArrayList<Mat> src_channels = new ArrayList<Mat>(); ArrayList<Mat> dst_channels = new ArrayList<Mat>(); Core.split(src, src_channels); Core.split(dst, dst_channels);/*from ww w .j a v a 2s. c o m*/ for (int i = 0; i < 3; i++) { MatOfDouble src_mean = new MatOfDouble(), src_std = new MatOfDouble(); MatOfDouble dst_mean = new MatOfDouble(), dst_std = new MatOfDouble(); Core.meanStdDev(src_channels.get(i), src_mean, src_std); Core.meanStdDev(dst_channels.get(i), dst_mean, dst_std); dst_channels.get(i).convertTo(dst_channels.get(i), CvType.CV_64FC1); Core.subtract(dst_channels.get(i), dst_mean, dst_channels.get(i)); Core.divide(dst_std, src_std, dst_std); Core.multiply(dst_channels.get(i), dst_std, dst_channels.get(i)); Core.add(dst_channels.get(i), src_mean, dst_channels.get(i)); dst_channels.get(i).convertTo(dst_channels.get(i), CvType.CV_8UC1); } Core.merge(dst_channels, dst); Imgproc.cvtColor(dst, dst, Imgproc.COLOR_Lab2BGR); return dst; }
From source file:edu.soict.hust.k57.mmdb.components.HistogramCaculator.java
@Override public void accept(ImgEnt t) { System.loadLibrary(Core.NATIVE_LIBRARY_NAME); Mat mat = Mat.eye(3, 3, CvType.CV_8UC1); Mat m = Imgcodecs.imread(t.getF().getPath()); List<Mat> images = new ArrayList<Mat>(); Core.split(m, images); MatOfInt histSize = new MatOfInt(t.getBin()); // kch thc ca histogram MatOfInt channels = new MatOfInt(0); // Knh mu mun tnh MatOfFloat histRange = new MatOfFloat(0, 256); Mat bHist = new Mat(); Mat gHist = new Mat(); Mat rHist = new Mat(); Imgproc.calcHist(images.subList(0, 1), channels, new Mat(), bHist, histSize, histRange, false); Core.normalize(bHist, bHist, 0, 1, Core.NORM_MINMAX, -1, new Mat()); Imgproc.calcHist(images.subList(1, 2), channels, new Mat(), gHist, histSize, histRange, false); Core.normalize(gHist, gHist, 0, 1, Core.NORM_MINMAX, -1, new Mat()); Imgproc.calcHist(images.subList(2, 3), channels, new Mat(), rHist, histSize, histRange, false); Core.normalize(rHist, rHist, 0, 1, Core.NORM_MINMAX, -1, new Mat()); t.setbHistogram(bHist);//from w w w.j av a2 s . c om t.setgHistogram(gHist); t.setrHistogram(rHist); }
From source file:edu.sust.cse.util.Histogram.java
public static Mat getHistogram(Mat image) { try {/* w w w. ja va 2 s .c o m*/ Mat src = new Mat(image.height(), image.width(), CvType.CV_8UC2); Imgproc.cvtColor(image, src, Imgproc.COLOR_RGB2GRAY); ArrayList<Mat> bgr_planes = new ArrayList<>(); Core.split(src, bgr_planes); MatOfInt histSize = new MatOfInt(256); final MatOfFloat histRange = new MatOfFloat(0f, 256f); boolean accumulate = false; Mat b_hist = new Mat(); Imgproc.calcHist(bgr_planes, new MatOfInt(0), new Mat(), b_hist, histSize, histRange, accumulate); int hist_w = 512; int hist_h = 600; long bin_w; bin_w = Math.round((double) (hist_w / 256)); Mat histImage = new Mat(hist_h, hist_w, CvType.CV_8UC1); Core.normalize(b_hist, b_hist, 3, histImage.rows(), Core.NORM_MINMAX); for (int i = 1; i < 256; i++) { Core.line(histImage, new Point(bin_w * (i - 1), hist_h - Math.round(b_hist.get(i - 1, 0)[0])), new Point(bin_w * (i), hist_h - Math.round(Math.round(b_hist.get(i, 0)[0]))), new Scalar(255, 0, 0), 2, 8, 0); } return histImage; } catch (Exception ex) { System.out.println("[HISTOGRAM][ERROR][" + ex.getMessage() + "]"); return null; } }
From source file:es.ugr.osgiliart.features.opencv.Histogram.java
License:Open Source License
@Override public double[] extract(Mat image) { Mat hsvImage = new Mat(image.width(), image.height(), image.type()); Mat histHue = new Mat(); Mat histSaturation = new Mat(); Imgproc.cvtColor(image, hsvImage, Imgproc.COLOR_BGR2HSV); List<Mat> channels = new ArrayList<Mat>(); Core.split(hsvImage, channels); //Histogram for hue Imgproc.calcHist(Arrays.asList(new Mat[] { channels.get(0) }), new MatOfInt(0), new Mat(), histHue, new MatOfInt(BINS), new MatOfFloat(MIN_VALUE, MAX_VALUE)); //Histogram for saturation Imgproc.calcHist(Arrays.asList(new Mat[] { channels.get(1) }), new MatOfInt(0), new Mat(), histSaturation, new MatOfInt(BINS), new MatOfFloat(MIN_VALUE, MAX_VALUE)); double sum = Core.sumElems(histHue).val[0]; double[] values = new double[histHue.height() + histSaturation.height()]; int k = 0;//from w w w. j av a 2 s. c om for (int i = 0; i < histHue.height(); ++i) { values[k++] = histHue.get(i, 0)[0] / sum; } sum = Core.sumElems(histSaturation).val[0]; for (int i = 0; i < histSaturation.height(); ++i) { values[k++] = histSaturation.get(i, 0)[0] / sum; } return values; }