List of usage examples for org.opencv.core Scalar Scalar
public Scalar(double v0, double v1, double v2)
From source file:classes.TextRecognitionPreparer.java
private static Scalar getFillingColor(Scalar userColor, Mat cutout, Mat labels, Mat centers) { double minDistance = 1000000; Scalar fillingColor = null;//w w w. jav a2 s . c om centers.convertTo(centers, CvType.CV_8UC1, 255.0); centers.reshape(3); List<Mat> clusters = new ArrayList<Mat>(); for (int i = 0; i < centers.rows(); i++) { clusters.add(Mat.zeros(cutout.size(), cutout.type())); } Map<Integer, Integer> counts = new HashMap<Integer, Integer>(); for (int i = 0; i < centers.rows(); i++) { counts.put(i, 0); } int rows = 0; for (int y = 0; y < cutout.rows(); y++) { for (int x = 0; x < cutout.cols(); x++) { int label = (int) labels.get(rows, 0)[0]; int r = (int) centers.get(label, 2)[0]; int g = (int) centers.get(label, 1)[0]; int b = (int) centers.get(label, 0)[0]; counts.put(label, counts.get(label) + 1); clusters.get(label).put(y, x, b, g, r); rows++; } } Set<Integer> keySet = counts.keySet(); Iterator<Integer> iterator = keySet.iterator(); while (iterator.hasNext()) { int label = (int) iterator.next(); int r = (int) centers.get(label, 2)[0]; int g = (int) centers.get(label, 1)[0]; int b = (int) centers.get(label, 0)[0]; Scalar currentColor = new Scalar(r, g, b); double distance = getColorDistance(currentColor, userColor); if (distance < minDistance) { minDistance = distance; fillingColor = currentColor; } } return fillingColor; }
From source file:cn.xiongyihui.webcam.JpegFactory.java
License:Open Source License
public void onPreviewFrame(byte[] data, Camera camera) { YuvImage yuvImage = new YuvImage(data, ImageFormat.NV21, mWidth, mHeight, null); mJpegOutputStream.reset();/*from ww w . j a va 2 s. c o m*/ try { //Log.e(TAG, "Beginning to read values!"); double distanceTemplateFeatures = this.globalClass.getDistanceTemplateFeatures(); double xTemplateCentroid = this.globalClass.getXtemplateCentroid(); double yTemplateCentroid = this.globalClass.getYtemplateCentroid(); int x0template = this.globalClass.getX0display(); int y0template = this.globalClass.getY0display(); int x1template = this.globalClass.getX1display(); int y1template = this.globalClass.getY1display(); Mat templateDescriptor = this.globalClass.getTemplateDescriptor(); MatOfKeyPoint templateKeyPoints = this.globalClass.getKeyPoints(); KeyPoint[] templateKeyPointsArray = templateKeyPoints.toArray(); int numberOfTemplateFeatures = this.globalClass.getNumberOfTemplateFeatures(); int numberOfPositiveTemplateFeatures = this.globalClass.getNumberOfPositiveTemplateFeatures(); KeyPoint[] normalisedTemplateKeyPoints = this.globalClass.getNormalisedTemplateKeyPoints(); double normalisedXcentroid = this.globalClass.getNormalisedXcentroid(); double normalisedYcentroid = this.globalClass.getNormalisedYcentroid(); int templateCapturedBitmapWidth = this.globalClass.getTemplateCapturedBitmapWidth(); int templateCapturedBitmapHeight = this.globalClass.getTemplateCapturedBitmapHeight(); //Log.e(TAG, "Ended reading values!"); globalClass.setJpegFactoryDimensions(mWidth, mHeight); double scalingRatio, scalingRatioHeight, scalingRatioWidth; scalingRatioHeight = (double) mHeight / (double) templateCapturedBitmapHeight; scalingRatioWidth = (double) mWidth / (double) templateCapturedBitmapWidth; scalingRatio = (scalingRatioHeight + scalingRatioWidth) / 2; //Just to account for any minor variations. //Log.e(TAG, "Scaling ratio:" + String.valueOf(scalingRatio)); //Log.e("Test", "Captured Bitmap's dimensions: (" + templateCapturedBitmapHeight + "," + templateCapturedBitmapWidth + ")"); //Scale the actual features of the image int flag = this.globalClass.getFlag(); if (flag == 0) { int iterate = 0; int iterationMax = numberOfTemplateFeatures; for (iterate = 0; iterate < (iterationMax); iterate++) { Log.e(TAG, "Point detected " + iterate + ":(" + templateKeyPointsArray[iterate].pt.x + "," + templateKeyPointsArray[iterate].pt.y + ")"); if (flag == 0) { templateKeyPointsArray[iterate].pt.x = scalingRatio * (templateKeyPointsArray[iterate].pt.x + (double) x0template); templateKeyPointsArray[iterate].pt.y = scalingRatio * (templateKeyPointsArray[iterate].pt.y + (double) y0template); } Log.e(TAG, "Scaled points:(" + templateKeyPointsArray[iterate].pt.x + "," + templateKeyPointsArray[iterate].pt.y + ")"); } this.globalClass.setFlag(1); } templateKeyPoints.fromArray(templateKeyPointsArray); //Log.e(TAG, "Template-features have been scaled successfully!"); long timeBegin = (int) System.currentTimeMillis(); Mat mYuv = new Mat(mHeight + mHeight / 2, mWidth, CvType.CV_8UC1); mYuv.put(0, 0, data); Mat mRgb = new Mat(); Imgproc.cvtColor(mYuv, mRgb, Imgproc.COLOR_YUV420sp2RGB); Mat result = new Mat(); Imgproc.cvtColor(mRgb, result, Imgproc.COLOR_RGB2GRAY); int detectorType = FeatureDetector.ORB; FeatureDetector featureDetector = FeatureDetector.create(detectorType); MatOfKeyPoint keypointsImage = new MatOfKeyPoint(); featureDetector.detect(result, keypointsImage); KeyPoint[] imageKeypoints = keypointsImage.toArray(); Scalar color = new Scalar(0, 0, 0); DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.ORB); Mat imageDescriptor = new Mat(); descriptorExtractor.compute(result, keypointsImage, imageDescriptor); //BRUTEFORCE_HAMMING apparently finds even the suspicious feature-points! So, inliers and outliers can turn out to be a problem DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING); MatOfDMatch matches = new MatOfDMatch(); matcher.match(imageDescriptor, templateDescriptor, matches); //Log.e("Prasad", String.valueOf(mWidth) + "," + String.valueOf(mHeight)); DMatch[] matchesArray = matches.toArray(); double minimumMatchDistance = globalClass.getHammingDistance(); int iDescriptorMax = matchesArray.length; int iterateDescriptor; double xMatchedPoint, yMatchedPoint; int flagDraw = Features2d.NOT_DRAW_SINGLE_POINTS; Point point; double rHigh = this.globalClass.getRhigh(); double rLow = this.globalClass.getRlow(); double gHigh = this.globalClass.getGhigh(); double gLow = this.globalClass.getGlow(); double bHigh = this.globalClass.getBhigh(); double bLow = this.globalClass.getBlow(); double[] colorValue; double red, green, blue; int[] featureCount; double xKernelSize = 9, yKernelSize = 9; globalClass.setKernelSize(xKernelSize, yKernelSize); double xImageKernelScaling, yImageKernelScaling; xImageKernelScaling = xKernelSize / mWidth; yImageKernelScaling = yKernelSize / mHeight; int[][] kernel = new int[(int) xKernelSize][(int) yKernelSize]; double[][] kernelCounter = new double[(int) xKernelSize][(int) yKernelSize]; int numberKernelMax = 10; globalClass.setNumberKernelMax(numberKernelMax); int[][][] kernelArray = new int[(int) xKernelSize][(int) yKernelSize][numberKernelMax]; double featureImageResponse; double xImageCentroid, yImageCentroid; double xSum = 0, ySum = 0; double totalImageResponse = 0; for (iterateDescriptor = 0; iterateDescriptor < iDescriptorMax; iterateDescriptor++) { if (matchesArray[iterateDescriptor].distance < minimumMatchDistance) { //MatchedPoint: Awesome match without color feedback xMatchedPoint = imageKeypoints[matchesArray[iterateDescriptor].queryIdx].pt.x; yMatchedPoint = imageKeypoints[matchesArray[iterateDescriptor].queryIdx].pt.y; colorValue = mRgb.get((int) yMatchedPoint, (int) xMatchedPoint); red = colorValue[0]; green = colorValue[1]; blue = colorValue[2]; int xKernelFeature, yKernelFeature; //Color feedback if ((rLow < red) & (red < rHigh) & (gLow < green) & (green < gHigh) & (bLow < blue) & (blue < bHigh)) { try { featureImageResponse = imageKeypoints[matchesArray[iterateDescriptor].queryIdx].response; if (featureImageResponse > 0) { xSum = xSum + featureImageResponse * xMatchedPoint; ySum = ySum + featureImageResponse * yMatchedPoint; totalImageResponse = totalImageResponse + featureImageResponse; point = imageKeypoints[matchesArray[iterateDescriptor].queryIdx].pt; xKernelFeature = (int) (xMatchedPoint * xImageKernelScaling); yKernelFeature = (int) (yMatchedPoint * yImageKernelScaling); kernelCounter[xKernelFeature][yKernelFeature]++; //Core.circle(result, point, 3, color); } } catch (Exception e) { } } //Log.e(TAG, iterateDescriptor + ": (" + xMatchedPoint + "," + yMatchedPoint + ")"); } } int iKernel = 0, jKernel = 0; for (iKernel = 0; iKernel < xKernelSize; iKernel++) { for (jKernel = 0; jKernel < yKernelSize; jKernel++) { if (kernelCounter[iKernel][jKernel] > 0) { kernel[iKernel][jKernel] = 1; } else { kernel[iKernel][jKernel] = 0; } } } xImageCentroid = xSum / totalImageResponse; yImageCentroid = ySum / totalImageResponse; if ((Double.isNaN(xImageCentroid)) | (Double.isNaN(yImageCentroid))) { //Log.e(TAG, "Centroid is not getting detected! Increasing hamming distance (error-tolerance)!"); globalClass.setHammingDistance((int) (minimumMatchDistance + 2)); } else { //Log.e(TAG, "Centroid is getting detected! Decreasing and optimising hamming (error-tolerance)!"); globalClass.setHammingDistance((int) (minimumMatchDistance - 1)); int jpegCount = globalClass.getJpegFactoryCallCount(); jpegCount++; globalClass.setJpegFactoryCallCount(jpegCount); int initialisationFlag = globalClass.getInitialisationFlag(); int numberOfDistances = 10; globalClass.setNumberOfDistances(numberOfDistances); if ((jpegCount > globalClass.getNumberKernelMax()) & (jpegCount > numberOfDistances)) { globalClass.setInitialisationFlag(1); } int[][] kernelSum = new int[(int) xKernelSize][(int) yKernelSize], mask = new int[(int) xKernelSize][(int) yKernelSize]; int iJpeg, jJpeg; kernelSum = globalClass.computeKernelSum(kernel); Log.e(TAG, Arrays.deepToString(kernelSum)); for (iJpeg = 0; iJpeg < xKernelSize; iJpeg++) { for (jJpeg = 0; jJpeg < yKernelSize; jJpeg++) { if (kernelSum[iJpeg][jJpeg] > (numberKernelMax / 4)) {//Meant for normalised kernel mask[iJpeg][jJpeg]++; } } } Log.e(TAG, Arrays.deepToString(mask)); int maskedFeatureCount = 1, xMaskFeatureSum = 0, yMaskFeatureSum = 0; for (iJpeg = 0; iJpeg < xKernelSize; iJpeg++) { for (jJpeg = 0; jJpeg < yKernelSize; jJpeg++) { if (mask[iJpeg][jJpeg] == 1) { xMaskFeatureSum = xMaskFeatureSum + iJpeg; yMaskFeatureSum = yMaskFeatureSum + jJpeg; maskedFeatureCount++; } } } double xMaskMean = xMaskFeatureSum / maskedFeatureCount; double yMaskMean = yMaskFeatureSum / maskedFeatureCount; double xSquaredSum = 0, ySquaredSum = 0; for (iJpeg = 0; iJpeg < xKernelSize; iJpeg++) { for (jJpeg = 0; jJpeg < yKernelSize; jJpeg++) { if (mask[iJpeg][jJpeg] == 1) { xSquaredSum = xSquaredSum + (iJpeg - xMaskMean) * (iJpeg - xMaskMean); ySquaredSum = ySquaredSum + (jJpeg - yMaskMean) * (jJpeg - yMaskMean); } } } double xRMSscaled = Math.sqrt(xSquaredSum); double yRMSscaled = Math.sqrt(ySquaredSum); double RMSimage = ((xRMSscaled / xImageKernelScaling) + (yRMSscaled / yImageKernelScaling)) / 2; Log.e(TAG, "RMS radius of the image: " + RMSimage); /*//Command the quadcopter and send PWM values to Arduino double throttlePWM = 1500, yawPWM = 1500, pitchPWM = 1500; double deltaThrottle = 1, deltaYaw = 1, deltaPitch = 1; throttlePWM = globalClass.getThrottlePWM(); pitchPWM = globalClass.getPitchPWM(); yawPWM = globalClass.getYawPWM(); deltaThrottle = globalClass.getThrottleDelta(); deltaPitch = globalClass.getPitchDelta(); deltaYaw = globalClass.getYawDelta(); if(yImageCentroid>yTemplateCentroid) { throttlePWM = throttlePWM + deltaThrottle; }else{ throttlePWM = throttlePWM - deltaThrottle; } if(RMSimage>distanceTemplateFeatures) { pitchPWM = pitchPWM + deltaPitch; }else{ pitchPWM = pitchPWM - deltaPitch; } if(xImageCentroid>xTemplateCentroid) { yawPWM = yawPWM + deltaYaw; }else{ yawPWM = yawPWM - deltaYaw; } if(1000>throttlePWM){ throttlePWM = 1000; } if(2000<throttlePWM){ throttlePWM = 2000; } if(1000>pitchPWM){ pitchPWM = 1000; } if(2000<pitchPWM){ pitchPWM = 2000; } if(1000>yawPWM){ yawPWM = 1000; } if(2000<yawPWM){ yawPWM = 2000; } globalClass.setPitchPWM(pitchPWM); globalClass.setYawPWM(yawPWM); globalClass.setThrottlePWM(throttlePWM);*/ //Display bounding circle int originalWidthBox = x1template - x0template; int originalHeightBox = y1template - y0template; double scaledBoundingWidth = (originalWidthBox * RMSimage / distanceTemplateFeatures); double scaledBoundingHeight = (originalHeightBox * RMSimage / distanceTemplateFeatures); double displayRadius = (scaledBoundingWidth + scaledBoundingHeight) / 2; displayRadius = displayRadius * 1.4826; displayRadius = displayRadius / numberKernelMax; double distanceAverage = 0; if (Double.isNaN(displayRadius)) { //Log.e(TAG, "displayRadius is NaN!"); } else { distanceAverage = globalClass.imageDistanceAverage(displayRadius); //Log.e(TAG, "Average distance: " + distanceAverage); } if ((Double.isNaN(xImageCentroid)) | Double.isNaN(yImageCentroid)) { //Log.e(TAG, "Centroid is NaN!"); } else { globalClass.centroidAverage(xImageCentroid, yImageCentroid); } if (initialisationFlag == 1) { //int displayRadius = 50; Point pointDisplay = new Point(); //pointDisplay.x = xImageCentroid; //pointDisplay.y = yImageCentroid; pointDisplay.x = globalClass.getXcentroidAverageGlobal(); pointDisplay.y = globalClass.getYcentroidAverageGlobal(); globalClass.centroidAverage(xImageCentroid, yImageCentroid); int distanceAverageInt = (int) distanceAverage; Core.circle(result, pointDisplay, distanceAverageInt, color); } } Log.e(TAG, "Centroid in the streamed image: (" + xImageCentroid + "," + yImageCentroid + ")"); /*try { //Features2d.drawKeypoints(result, keypointsImage, result, color, flagDraw); Features2d.drawKeypoints(result, templateKeyPoints, result, color, flagDraw); }catch(Exception e){}*/ //Log.e(TAG, "High (R,G,B): (" + rHigh + "," + gHigh + "," + bHigh + ")"); //Log.e(TAG, "Low (R,G,B): (" + rLow + "," + gLow + "," + bLow + ")"); //Log.e(TAG, Arrays.toString(matchesArray)); try { Bitmap bmp = Bitmap.createBitmap(result.cols(), result.rows(), Bitmap.Config.ARGB_8888); Utils.matToBitmap(result, bmp); //Utils.matToBitmap(mRgb, bmp); bmp.compress(Bitmap.CompressFormat.JPEG, mQuality, mJpegOutputStream); } catch (Exception e) { Log.e(TAG, "JPEG not working!"); } long timeEnd = (int) System.currentTimeMillis(); Log.e(TAG, "Time consumed is " + String.valueOf(timeEnd - timeBegin) + "milli-seconds!"); mJpegData = mJpegOutputStream.toByteArray(); synchronized (mJpegOutputStream) { mJpegOutputStream.notifyAll(); } } catch (Exception e) { Log.e(TAG, "JPEG-factory is not working!"); } }
From source file:com.astrocytes.core.operationsengine.OperationsImpl.java
License:Open Source License
@Deprecated private Mat drawAstrocyteCenters() { if (astrocytesCenters == null) { return sourceImage; }/* www .ja v a2 s . c o m*/ Mat result = sourceImage.clone(); Scalar color = new Scalar(108, 240, 3); for (Point center : astrocytesCenters) { Imgproc.circle(result, center, 3, color); } return result; }
From source file:com.astrocytes.core.operationsengine.OperationsImpl.java
License:Open Source License
@Deprecated private Mat drawNeuronsCenters(Mat src) { if (src == null) { src = sourceImage.clone();/* ww w .ja v a2 s .c o m*/ } if (neurons == null) { return src; } Mat result = src.clone(); Scalar color = new Scalar(250, 10, 19); for (Neuron neuron : neurons) { Imgproc.circle(result, neuron.getCenter(), 4, color, 2); } return result; }
From source file:com.astrocytes.core.operationsengine.OperationsImpl.java
License:Open Source License
@Deprecated private Mat drawLayerBounds() { if (layerBounds == null) { return sourceImage; }/*from w w w . j a v a 2s. c om*/ Mat result = sourceImage.clone(); for (int i = 0; i < layerBounds.rows(); i++) { Scalar color = new Scalar(250, 20, 18); if (i == 0 || i == layerBounds.rows() - 1) { color = new Scalar(18, 20, 250); } for (int j = 0; j < layerBounds.cols(); j++) { Imgproc.circle(result, new Point(j, layerBounds.get(i, j)[0]), 1, color, -1); } } return result; }
From source file:com.carver.paul.truesight.ImageRecognition.ImageTools.java
License:Open Source License
public static void drawLinesOnImage(Mat lines, Mat image) { for (int i = 0; i < lines.rows(); i++) { double[] val = lines.get(i, 0); Imgproc.line(image, new Point(val[0], val[1]), new Point(val[2], val[3]), new Scalar(0, 255, 0), 2); }/*from w ww . j a va 2 s .c o m*/ }
From source file:com.carver.paul.truesight.ImageRecognition.RecognitionModel.java
License:Open Source License
public static List<Mat> findHeroTopLinesInImage(Mat photo, List<List<Integer>> colourRanges, int lowerHsvS, int lowerHsvV, int upperHsvS, int upperHsvV) { List<Mat> linesList = new ArrayList<>(); int pos = 0;// www. j a v a 2 s .co m int photoWidth = photo.width(); for (List<Integer> colourRange : colourRanges) { int minX; int maxX; if (colourRanges.size() == 1) { minX = 0; maxX = photoWidth; } else { minX = pos * photoWidth / 6; maxX = (2 + pos) * photoWidth / 6; } Scalar lowerHsv = new Scalar(colourRange.get(0), lowerHsvS, lowerHsvV); Scalar upperHsv = new Scalar(colourRange.get(1), upperHsvS, upperHsvV); Mat subMat = photo.submat(0, photo.height() / 2, minX, maxX); Mat mask = new Mat(); ImageTools.MaskAColourFromImage(subMat, lowerHsv, upperHsv, mask); Mat lines = new Mat(); // note, this is the part that takes most time. ImageTools.getLineFromTopRectMask(mask, lines, photoWidth / 7); //USED TO BE 8!!!! adjustXPosOfLines(lines, minX); linesList.add(lines); // Main.DrawMatInImageBox(mask, maskImage); // just for debug pos++; } return linesList; }
From source file:com.carver.paul.truesight.ImageRecognition.RecognitionModel.java
License:Open Source License
/** * Draws the line onto the image, used for debugging. * @param img/*from ww w . j a v a2 s . c o m*/ */ public void Draw(Mat img) { Imgproc.rectangle(img, new org.opencv.core.Point(rect.left, rect.top), new org.opencv.core.Point(rect.right, rect.bottom), new Scalar(0, 255, 0), 2); }
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();//from w w w .j av a2 s. com // 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; }
From source file:com.example.sarthuak.opencv.MainActivity.java
public Mat onCameraFrame(CvCameraViewFrame inputFrame) { // TODO Auto-generated method stub final int viewMode = mViewMode; switch (viewMode) { case VIEW_MODE_RGBA: // input frame has RBGA format mRgba = inputFrame.rgba();//from ww w. j ava 2s . c o m break; case VIEW_MODE_CANNY: // input frame has gray scale format mRgba = inputFrame.rgba(); Imgproc.Canny(inputFrame.gray(), mRgbaF, 80, 100); Imgproc.cvtColor(mRgbaF, mRgba, Imgproc.COLOR_GRAY2RGBA, 4); break; case VIEW_MODE_ocr: startActivity(new Intent(this, ScanLicensePlateActivity.class)); break; case VIEW_MODE_new: Mat mRgba; mRgba = inputFrame.rgba(); drawing = mRgba.clone(); mRgbaT = drawing; Imgproc.cvtColor(drawing, mRgbaT, Imgproc.COLOR_BGR2GRAY); org.opencv.core.Size s = new Size(1, 1); Imgproc.GaussianBlur(mRgbaT, mRgbaT, s, 0, 0); Imgproc.Canny(mRgbaT, mRgbaT, 100, 255); Mat element = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(5, 5)); Imgproc.dilate(mRgbaT, mRgbaT, element); List<MatOfPoint> contours = new ArrayList<>(); Imgproc.findContours(drawing, contours, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE, new Point(0, 0)); double maxArea = -1; int maxAreaIdx = -1; for (int idx = 0; idx < contours.size(); idx++) { Mat contour = contours.get(idx); double contourarea = Imgproc.contourArea(contour); if (contourarea > maxArea) { maxArea = contourarea; maxAreaIdx = idx; } } Imgproc.drawContours(mRgba, contours, maxAreaIdx, new Scalar(255, 0, 0), 5); } return mRgba; // This function must return }