public void Process(Mat rgbaImage) { Log.Info(TAG, "Process rgbaImages"); Imgproc.PyrDown(rgbaImage, mPyrDownMat); Imgproc.PyrDown(mPyrDownMat, mPyrDownMat); Imgproc.CvtColor(mPyrDownMat, mHsvMat, Imgproc.ColorRgb2hsvFull); Core.InRange(mHsvMat, mLowerBound, mUpperBound, mMask); Imgproc.Dilate(mMask, mDilatedMask, new Mat()); IList <MatOfPoint> contours = new JavaList <MatOfPoint>(); Imgproc.FindContours(mDilatedMask, contours, mHierarchy, Imgproc.RetrExternal, Imgproc.ChainApproxSimple); // Find max contour area double maxArea = 0; foreach (var each in contours) { MatOfPoint wrapper = each; double area = Imgproc.ContourArea(wrapper); if (area > maxArea) { maxArea = area; } Log.Info(TAG, "Process rgbaImages\t-- Imgproc.ContourArea(wrapper)"); } // Filter contours by area and resize to fit the original image size mContours.Clear(); foreach (var each in contours) { MatOfPoint contour = each; if (Imgproc.ContourArea(contour) > mMinContourArea * maxArea) { Core.Multiply(contour, new Scalar(4, 4), contour); mContours.Add(contour); Log.Info(TAG, "Process rgbaImages\t-- mContours.Add(contour)"); } } }
public static async Task <string> detectAndExtractText(Bitmap img) { //Matrix für die Bilder Mat large = new Mat(); Mat small = new Mat(); Mat rgb = new Mat(); //Bild zu Matrix umwandeln Utils.BitmapToMat(img, large); // downsample and use it for processing Imgproc.PyrDown(large, rgb); //Grey Imgproc.CvtColor(rgb, small, Imgproc.ColorBgr2gray); //Gradiant Mat grad = new Mat(); Size morphsize = new Size(3.0, 3.0); Mat morphKernel = Imgproc.GetStructuringElement(Imgproc.MorphEllipse, morphsize); Imgproc.MorphologyEx(small, grad, Imgproc.MorphGradient, morphKernel); //Binarize Mat bw = new Mat(); Imgproc.Threshold(grad, bw, 0.0, 255.0, Imgproc.ThreshBinary | Imgproc.ThreshOtsu); // connect horizontally oriented regions Mat connected = new Mat(); Size connectsize = new Size(9.0, 1.0); morphKernel = Imgproc.GetStructuringElement(Imgproc.MorphRect, connectsize); Imgproc.MorphologyEx(bw, connected, Imgproc.MorphClose, morphKernel); // find contours Mat mask = Mat.Zeros(bw.Size(), CvType.Cv8uc1); JavaList <MatOfPoint> contours = new JavaList <MatOfPoint>(); Mat hierarchy = new Mat(); OpenCV.Core.Point contourPoint = new OpenCV.Core.Point(0, 0); Imgproc.FindContours(connected, contours, hierarchy, Imgproc.RetrCcomp, Imgproc.ChainApproxSimple, contourPoint); Scalar zero = new Scalar(0, 0, 0); Scalar contourscal = new Scalar(255, 255, 255); Scalar rectScalar = new Scalar(0, 255, 0); OpenCV.Core.Rect rect; Mat maskROI; double r; double[] contourInfo; string resulttext = ""; string part; Bitmap bmpOcr; Mat croppedPart; for (int i = 0; i >= 0;) { rect = Imgproc.BoundingRect(contours[i]); maskROI = new Mat(mask, rect); maskROI.SetTo(zero); //fill the contour Imgproc.DrawContours(mask, contours, i, contourscal, Core.Filled); // ratio of non-zero pixels in the filled region r = (double)Core.CountNonZero(maskROI) / (rect.Width * rect.Height); /* assume at least 45% of the area is filled if it contains text */ /* constraints on region size */ /* these two conditions alone are not very robust. better to use something * like the number of significant peaks in a horizontal projection as a third condition */ if (r > .45 && (rect.Height > 8 && rect.Width > 8)) { //Imgproc.Rectangle(rgb, rect.Br(), rect.Tl(), rectScalar, 2); try { croppedPart = rgb.Submat(rect); bmpOcr = Bitmap.CreateBitmap(croppedPart.Width(), croppedPart.Height(), Bitmap.Config.Argb8888); Utils.MatToBitmap(croppedPart, bmpOcr); part = await OCR.getText(bmpOcr); resulttext = resulttext + part; Console.WriteLine("------------------Durchlauf-------------"); } catch (Exception e) { Android.Util.Log.Debug("Fehler", "cropped part data error " + e.Message); } } //Nächste Element bestimmen contourInfo = hierarchy.Get(0, i); i = (int)contourInfo[0]; } return(resulttext); }