/// <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;
}
/// <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 KMeansAlgorithm(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();
}
/// <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)));
}