Dilatation operator from Mathematical Morphology with 3x3 structuring element.

The filter represents an optimized version of Dilatation filter, which is aimed for grayscale image processing with 3x3 structuring element.

See Dilatation filter, which represents generic version of dilatation filter supporting custom structuring elements and wider range of image formats.

The filter accepts 8 bpp grayscale images for processing.

Inheritance: BaseUsingCopyPartialFilter
Dilatation3x3 Class Documentation
Exemplo n.º 1
0
        static void Main(string[] args)
        {
            Threshold thresh = new Threshold(10);
            Median median = new Median(9);
            Erosion3x3 erode = new Erosion3x3();
            Dilatation3x3 dilate = new Dilatation3x3();
            GrahamConvexHull hullFinder = new GrahamConvexHull();
            ConnectedComponentsLabeling ccLabeler = new ConnectedComponentsLabeling();
            BorderFollowing contourFinder = new BorderFollowing();
            GrayscaleToRGB rgb = new GrayscaleToRGB();
            ConvexHullDefects defectFinder = new ConvexHullDefects(10);

            Bitmap img = (Bitmap)Bitmap.FromFile("hand3.jpg");

            Bitmap image = Grayscale.CommonAlgorithms.BT709.Apply(img);
            thresh.ApplyInPlace(image);
            //median.ApplyInPlace(image);
            erode.ApplyInPlace(image);
            dilate.ApplyInPlace(image);

            BlobCounter counter = new BlobCounter(image);
            counter.ObjectsOrder = ObjectsOrder.Area;

            Blob[] blobs = counter.GetObjectsInformation();

            if (blobs.Length > 0)
            {
                counter.ExtractBlobsImage(image, blobs[0], true);

                UnmanagedImage hand = blobs[0].Image;

                var contour = contourFinder.FindContour(hand);

                if (contour.Count() > 0)
                {
                    var initialHull = hullFinder.FindHull(contour);

                    var defects = defectFinder.FindDefects(contour, initialHull);

                    var filteredHull = initialHull.ClusterHullPoints().FilterLinearHullPoints();

                    var palmCenter = defects.Centroid(contour);

                    var wristPoints = filteredHull.SelectWristPoints(defects, contour);

                    Bitmap color = rgb.Apply(hand).ToManagedImage();

                    //BitmapData data = color.LockBits(new Rectangle(0, 0, color.Width, color.Height), ImageLockMode.ReadWrite, color.PixelFormat);
                    //Drawing.Polyline(data, contour, Color.Blue);
                    //Drawing.Polygon(data, filteredHull, Color.Red);
                    //color.UnlockBits(data);

                    Graphics gr = Graphics.FromImage(color);

                    gr.DrawPolygon(new Pen(Brushes.Red, 3), filteredHull.ToPtArray());
                    gr.DrawLines(new Pen(Brushes.Blue, 3), contour.ToPtArray());
                    gr.DrawEllipse(new Pen(Brushes.Red, 3), palmCenter.X - 10, palmCenter.Y - 10, 20, 20);

                    foreach (ConvexityDefect defect in defects)
                    {
                        gr.DrawEllipse(new Pen(Brushes.Green, 6), contour[defect.Point].X - 10, contour[defect.Point].Y - 10, 20, 20);
                    }

                    foreach (AForge.IntPoint pt in filteredHull)
                    {
                        gr.DrawEllipse(new Pen(Brushes.Yellow, 6), pt.X - 10, pt.Y - 10, 20, 20);
                    }

                    foreach (AForge.IntPoint pt in wristPoints)
                    {
                        gr.DrawEllipse(new Pen(Brushes.PowderBlue, 6), pt.X - 10, pt.Y - 10, 20, 20);
                    }

                    ImageBox.Show(color);
                }
            }
        }