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);
}
