private IplImage FeatureDetector(Bitmap bitmapIn)
{
double minVal, maxVal;
IplImage i1 = BitmapConverter.ToIplImage(bitmapIn);
IplImage gray = new IplImage(new OpenCvSharp.CvSize(i1.Size.Width, i1.Size.Height), BitDepth.U8, 1);
IplImage blur = new IplImage(new OpenCvSharp.CvSize(i1.Size.Width, i1.Size.Height), BitDepth.U8, 1);
IplImage gaussian = new IplImage(new OpenCvSharp.CvSize(i1.Size.Width, i1.Size.Height), BitDepth.U8, 1);
IplImage laplace = new IplImage(new OpenCvSharp.CvSize(i1.Size.Width, i1.Size.Height), BitDepth.F32, gaussian.NChannels);
IplImage converted = new IplImage(new OpenCvSharp.CvSize(i1.Size.Width, i1.Size.Height), BitDepth.U8, 1);
IplImage normalized = new IplImage(new OpenCvSharp.CvSize(i1.Size.Width, i1.Size.Height), BitDepth.U8, 1);
IplImage tresh = new IplImage(new OpenCvSharp.CvSize(i1.Size.Width, i1.Size.Height), BitDepth.U8, 1);
OpenCvSharp.Cv.CvtColor(i1, gray, ColorConversion.RgbToGray);
OpenCvSharp.Cv.Normalize(gray, normalized, 0.0, 255.0, NormType.MinMax);
OpenCvSharp.Cv.Smooth(normalized, blur, SmoothType.Median, 5, 5);
OpenCvSharp.Cv.Smooth(blur, gaussian, SmoothType.Gaussian, 5, 5);
OpenCvSharp.Cv.Laplace(gaussian, laplace, ApertureSize.Size5);
laplace.MinMaxLoc(out minVal, out maxVal);
laplace.ConvertScale(converted, 255.0 / (2.0 * maxVal), 128);
OpenCvSharp.Cv.Threshold(converted, tresh, 150.0, 255.0, ThresholdType.Binary);
return tresh;
}
