ienProc->ConvertToBWOrderd();  //convert to BW by dithering ordered
ienProc->RemoveIsolatedPixels(0, 5); // remove black isolated pixels (max 5 grouped)
ienProc->RemoveNoise(1, false); // remove noise, 1 iteration

procedure TForm1.EdgeDetect1Click(Sender: TObject);
{ Perform an edge detect using Sobel filter }
begin
  ImageEnView2.Assign(ImageEnView1);
  ImageEnView2.Proc.SaveUndo();
  { Perform an edge detect using Sobel filter }
  ImageEnView2.Proc.EdgeDetect_Sobel;
  { ConvertToBWThreshold to make result black/white (with 1=edge) }
  ImageEnView2.Proc.ConvertToBWThreshold(-2);
  ImageEnView2.Fit;
end;

procedure TForm1.EdgeDetect2Click(Sender: TObject);
begin
  ImageEnView3.Assign(ImageEnView1);
  ImageEnView3.Proc.SaveUndo();
  { EdgeDetect_ShenCastan converts the current color image to black/white
  (1 bit) with a Shen-Castan (ISEF) edge detection algorithm.

  Shen-Castan algorithm convolves the image with the Infinite Symmetric
  Exponential Filter, computes the binary Laplacian image, suppresses false
  zero crossing, performs adaptive gradient thresholding, and, finally, also
  applies hysteresis thresholding. (Algorithms for Image Processing and
  Computer Vision - J.R.Parker).

  procedure EdgeDetect_ShenCastan(Ratio:double; Smooth:double; WindowSize:
    Integer; ThinFactor: Integer; DoHysteresis: Boolean);
  Ratio: percent of pixels to be above High threshold (suggested 0.99)
  Smooth: Smoothing factor (suggested 0.9)
  WindowSize: Size of window for adaptive gradient (suggested 7)
  ThinFactor: Thinning factor (suggested 0)
  DoHysteresis: If True turn on the hysteresis thresholding (suggested True) }

  ImageEnView3.Proc.EdgeDetect_ShenCastan(0.99, 0.9, 7, 0, True);
  ImageEnView3.Fit;
end;