Exemplo n.º 1
0
        /// <summary>
        /// Calculates the centroids of the clusters
        /// </summary>
        public void CalculateClusterCentroids()
        {
            //Console.WriteLine("Cluster Centroid calculation:");
            for (int j = 0; j < this.Clusters.Count; j++)
            {
                ClusterCentroid c = this.Clusters[j];
                double          l = 0.0;
                c.PixelCount    = 1;
                c.RSum          = 0;
                c.GSum          = 0;
                c.BSum          = 0;
                c.MembershipSum = 0;

                for (int i = 0; i < this.Points.Count; i++)
                {
                    ClusterPoint p = this.Points[i];
                    l                = Math.Pow(U[i, j], this.Fuzzyness);
                    c.RSum          += l * p.PixelColor.R;
                    c.GSum          += l * p.PixelColor.G;
                    c.BSum          += l * p.PixelColor.B;
                    c.MembershipSum += l;

                    if (U[i, j] == p.ClusterIndex)
                    {
                        c.PixelCount += 1;
                    }
                }

                c.PixelColor = Color.FromArgb((byte)(c.RSum / c.MembershipSum), (byte)(c.GSum / c.MembershipSum), (byte)(c.BSum / c.MembershipSum));
            }

            //update the original image
            Bitmap tempImage = new Bitmap(myImageWidth, myImageHeight, PixelFormat.Format32bppRgb);

            for (int j = 0; j < this.Points.Count; j++)
            {
                for (int i = 0; i < this.Clusters.Count; i++)
                {
                    ClusterPoint p = this.Points[j];
                    if (U[j, i] == p.ClusterIndex)
                    {
                        tempImage.SetPixel((int)p.X, (int)p.Y, this.Clusters[i].PixelColor);
                    }
                }
            }

            processedImage = tempImage;
        }
Exemplo n.º 2
0
        /// <summary>
        /// Initialize the algorithm with points and initial clusters
        /// </summary>
        /// <param name="points">The list of Points objects</param>
        /// <param name="clusters">The list of Clusters objects</param>
        /// <param name="fuzzy">The fuzzyness factor to be used, constant</param>
        /// <param name="myImage">A working image, so that the GUI working image can be updated</param>
        /// <param name="numCluster">The number of clusters requested by the user from the GUI</param>
        public FCM(List <ClusterPoint> points, List <ClusterCentroid> clusters, float fuzzy, Bitmap myImage, int numCluster)
        {
            if (points == null)
            {
                throw new ArgumentNullException("points");
            }

            if (clusters == null)
            {
                throw new ArgumentNullException("clusters");
            }


            processedImage = (Bitmap)myImage.Clone();


            this.Points        = points;
            this.Clusters      = clusters;
            this.myImageHeight = myImage.Height;
            this.myImageWidth  = myImage.Width;
            this.myImage       = new Bitmap(myImageWidth, myImageHeight, PixelFormat.Format32bppRgb);
            U = new double[this.Points.Count, this.Clusters.Count];
            this.Fuzzyness = fuzzy;

            double diff;

            // Iterate through all points to create initial U matrix
            for (int i = 0; i < this.Points.Count; i++)
            {
                ClusterPoint p   = this.Points[i];
                double       sum = 0.0;

                for (int j = 0; j < this.Clusters.Count; j++)
                {
                    ClusterCentroid c = this.Clusters[j];
                    diff    = Math.Sqrt(Math.Pow(CalculateEuclideanDistance(p, c), 2.0));
                    U[i, j] = (diff == 0) ? Eps : diff;
                    sum    += U[i, j];
                }
            }

            this.RecalculateClusterMembershipValues();
        }
Exemplo n.º 3
0
 /// <summary>
 /// Calculates Euclidean Distance distance between a point and a cluster centroid
 /// </summary>
 /// <param name="p">Point</param>
 /// <param name="c">Centroid</param>
 /// <returns>Calculated distance</returns>
 private double CalculateEuclideanDistance(ClusterPoint p, ClusterCentroid c)
 {
     return Math.Sqrt(Math.Pow(p.PixelColor.R - c.PixelColor.R, 2.0) + Math.Pow(p.PixelColor.G - c.PixelColor.G, 2.0) + Math.Pow(p.PixelColor.B - c.PixelColor.B, 2.0));
 }
Exemplo n.º 4
0
 /// <summary>
 /// Calculates Euclidean Distance distance between a point and a cluster centroid
 /// </summary>
 /// <param name="p">Point</param>
 /// <param name="c">Centroid</param>
 /// <returns>Calculated distance</returns>
 private double CalculateEuclideanDistance(ClusterPoint p, ClusterCentroid c)
 {
     return(Math.Sqrt(Math.Pow(p.PixelColor.R - c.PixelColor.R, 2.0) + Math.Pow(p.PixelColor.G - c.PixelColor.G, 2.0) + Math.Pow(p.PixelColor.B - c.PixelColor.B, 2.0)));
 }