Simple skeletonization filter.
The filter build simple objects' skeletons by thinning them until they have one pixel wide "bones" horizontally and vertically. The filter uses Background and Foreground colors to distinguish between object and background.
The filter accepts 8 bpp grayscale images for processing.
Sample usage:
// create filter SimpleSkeletonization filter = new SimpleSkeletonization( ); // apply the filter filter.ApplyInPlace( image ); Initial image:
Result image:
private void FillPictureBoxes(ref Bitmap image)
{
Bitmap tmpImg = image;
Bitmap tmpImg2 = image;
try
{
bool hasFilter = false;
//setup resize and filtersequesce
//resize img to fit picturebox
ResizeBicubic resizeFilter = new ResizeBicubic(0, 0);
resizeFilter = new ResizeBicubic(pbCapture.Width, pbCapture.Height);
tmpImg = resizeFilter.Apply(tmpImg);
resizeFilter = new ResizeBicubic(pbShapes.Width, pbShapes.Height);
tmpImg2 = resizeFilter.Apply(tmpImg2);
FiltersSequence processingFilter = new FiltersSequence();
//List all filters
IFilter ConservativeSmoothingFilter = new AForge.Imaging.Filters.ConservativeSmoothing();
IFilter InvertFilter = new AForge.Imaging.Filters.Invert();
IFilter HSLFilteringFilter = new AForge.Imaging.Filters.HSLFiltering();
IFilter SepiaFilter = new AForge.Imaging.Filters.Sepia();
IFilter grayscaleFilter = new AForge.Imaging.Filters.GrayscaleBT709();
IFilter SkeletonizationFilter = new AForge.Imaging.Filters.SimpleSkeletonization();
IFilter pixFilter = new AForge.Imaging.Filters.Pixellate();
////apply filter and process img---------------------------------------------
if (ConservativeSmoothing)
{
processingFilter.Add(ConservativeSmoothingFilter);
hasFilter = true;
}
if (Invert)
{
processingFilter.Add(InvertFilter);
hasFilter = true;
}
if (HSLswitch)
{
processingFilter.Add(HSLFilteringFilter);
hasFilter = true;
}
if (sepiaSwitch)
{
processingFilter.Add(SepiaFilter);
hasFilter = true;
}
if (Skeletonization)
{
processingFilter.Add(grayscaleFilter);
processingFilter.Add(SkeletonizationFilter);
hasFilter = true;
}
//apply the filter(s) to image
if (hasFilter)
{
//tmpImg = processingFilter.Apply(tmpImg);
tmpImg2 = processingFilter.Apply(tmpImg2);
}
processingFilter.Clear();
if (bwSwitch)
{
switchBandW(ref tmpImg);
}
if (CannyEdgeDetector)
{
// create filter
CannyEdgeDetector filter = new CannyEdgeDetector();
// apply the filter
tmpImg = Grayscale.CommonAlgorithms.BT709.Apply(tmpImg);
filter.ApplyInPlace(tmpImg);
// image = DrawFocusArea(gsImage);
}
else
{
// image = DrawFocusArea(image);
}
if (DifferenceEdgeDetector)
{
DifferenceEdgeDetector dFilter = new DifferenceEdgeDetector();
// apply the filter
tmpImg = Grayscale.CommonAlgorithms.BT709.Apply(tmpImg);
dFilter.ApplyInPlace(tmpImg);
}
if (HomogenityEdgeDetector)
{
HomogenityEdgeDetector hFilter = new HomogenityEdgeDetector();
// apply the filter
tmpImg = Grayscale.CommonAlgorithms.BT709.Apply(tmpImg);
hFilter.ApplyInPlace(tmpImg);
}
if (SobelEdgeDetector)
{
SobelEdgeDetector hFilter = new SobelEdgeDetector();
// apply the filter
tmpImg = Grayscale.CommonAlgorithms.BT709.Apply(tmpImg);
hFilter.ApplyInPlace(tmpImg);
BlobCounter bc = new BlobCounter(tmpImg);
Rectangle[] brecs = bc.GetObjectsRectangles();
//Graphics pg = Graphics.FromImage(tmpImg);
//Pen p = new Pen(Color.White, 2);
//foreach (Rectangle r in brecs)
//{
// pg.DrawRectangle(p, r);
//}
}
if (findShapes)
{
tmpImg = FindShapes(tmpImg, ref tmpImg2);
//ProcessImage(image);
}
else
{
pbCapture.Image = tmpImg; //set picturebox image----------------
pbShapes.Image = tmpImg2; //set picturebox image----------------
}
// Graphics g = Graphics.FromImage(tmpImg);
// Pen p = new Pen(Color.Red, 2);
// Rectangle lr = new Rectangle(100, 120, 80, 40);
//// Rectangle rr = new Rectangle(360, 220, 80, 40);
// g.DrawRectangle(p, lr);
// //g.DrawRectangle(p, rr);
}
catch (Exception ex)
{
MessageBox.Show(ex.Message);
}
// pbCapture.Image = tmpImg;//set picturebox image----------------
// pbShapes.Image = tmpImg2;//set picturebox image----------------
}
