private static int distance(ColorRGBModel a, ColorRGBModel b)
{
int dr = (a.R - b.R) * (a.R - b.R);
int db = (a.B - b.B) * (a.B - b.B);
int dg = (a.G - b.G) * (a.G - b.G);
return((int)Math.Sqrt(dr + db + dg));
}
private static int distance(ColorRGBModel a, int k)
{
int dr = (a.R - k) * (a.R - k);
int db = (a.B - k) * (a.B - k);
int dg = (a.G - k) * (a.G - k);
return((int)Math.Sqrt(dr + db + dg));
}
private static void newMean(int k, byte[,] kv, List <ColorRGBModel>[] cols, ref bool IsQuit)
{
for (int i = 0; i < k; i++)
{
ColorRGBModel kMeanValue = mean(cols[i]);
if (kv[i, 0] == kMeanValue.R && kv[i, 1] == kMeanValue.G && kv[i, 2] == kMeanValue.B)
{
IsQuit = true;
}
else
{
kv[i, 0] = kMeanValue.R;
kv[i, 1] = kMeanValue.G;
kv[i, 2] = kMeanValue.B;
IsQuit = false;
}
}
}
private static void KAddUp(int k, int width, int height, byte[, ,] martix, out List <ColorRGBModel>[] cols)
{
cols = new List <ColorRGBModel> [k];
for (int i = 0; i < k; i++)
{
cols[i] = new List <ColorRGBModel>();
}
for (int y = 0; y < height; y++)
{
for (int x = 0; x < width; x++)
{
int KPosition = martix[y, x, 0];
ColorRGBModel value = new ColorRGBModel();
value.R = martix[y, x, 1];
value.G = martix[y, x, 2];
value.B = martix[y, x, 3];
cols[KPosition].Add(value);
}
}
}
private static ColorRGBModel mean(List <ColorRGBModel> collections)
{
ColorRGBModel res = new ColorRGBModel();
if (!(collections.Count > 0))
{
return(res);
}
int r = 0, g = 0, b = 0;
foreach (ColorRGBModel c in collections)
{
r += c.R;
g += c.G;
b += c.B;
}
res.R = (byte)(r / collections.Count);
res.G = (byte)(g / collections.Count);
res.B = (byte)(b / collections.Count);
return(res);
}
