public double LikeAEllipse(List <Vector2> points)
{
foreach (Vector2 p in points)
{
mean += p;
}
mean /= points.Count;
float W = points.Count;
float[,] C = new float[2, 2];
foreach (Vector2 point in points)
{
C[0, 0] += (point.x - mean.x) * (point.x - mean.x);
C[0, 1] += (point.x - mean.x) * (point.y - mean.y);
C[1, 0] += (point.y - mean.y) * (point.x - mean.x);
C[1, 1] += (point.y - mean.y) * (point.y - mean.y);
}
C[0, 0] /= W;
C[0, 1] /= W;
C[1, 0] /= W;
C[1, 1] /= W;
Matrix2d CM = new Matrix2d(C);
double error = Mathf.Abs(W - 4 * Mathf.PI * Mathf.Sqrt(CM.Det()));
error /= W;
//Debug.Log("Like a ellipse error: " + error); //10^-2 may be a good threshold
return(error);
}
public double ErrorScore(List <MyVector2> points)
{
foreach (MyVector2 p in points)
{
mean += p;
}
mean /= points.Count;
double W = points.Count;
double[,] C = new double[2, 2];
foreach (MyVector2 point in points)
{
C[0, 0] += (point.x - mean.x) * (point.x - mean.x);
C[0, 1] += (point.x - mean.x) * (point.y - mean.y);
C[1, 0] += (point.y - mean.y) * (point.x - mean.x);
C[1, 1] += (point.y - mean.y) * (point.y - mean.y);
}
C[0, 0] /= W;
C[0, 1] /= W;
C[1, 0] /= W;
C[1, 1] /= W;
Matrix2d CM = new Matrix2d(C);
SVD svd = new SVD(C);
//svd.w - eigen value, start from 1
//svd.u - eigen vector, start from 1
int max = 1, min = 2;
if (svd.w[max] < svd.w[min])
{
int temp = max;
max = min;
min = temp;
}
double major = 2 * Math.Sqrt(svd.w[max]);
MyVector2 majoraxis = new MyVector2(svd.u[1, max], svd.u[2, max]);
majoraxis = majoraxis.Normalize();
double minor = 2 * Math.Sqrt(svd.w[min]);
MyVector2 minoraxis = new MyVector2(svd.u[1, min], svd.u[2, min]);
minoraxis = minoraxis.Normalize();
majorendp = mean + majoraxis * major;
majorstartp = mean - majoraxis * major;
minorendp = mean + minoraxis * minor;
minorstartp = mean - minoraxis * minor;
double error = Math.Abs(W - 4 * Math.PI * Math.Sqrt(CM.Det()));
error /= W;
Console.WriteLine("Like a ellipse error: {0}", error); //10^-2 may be a good threshold
return(error);
}
public double FitEllipse()
{
List <Vector2> points = IExtension.GetMaskPoints(img);
foreach (Vector2 p in points)
{
mean += p;
}
mean /= points.Count;
float W = points.Count;
float[,] C = new float[2, 2];
foreach (Vector2 point in points)
{
C[0, 0] += (point.x - mean.x) * (point.x - mean.x);
C[0, 1] += (point.x - mean.x) * (point.y - mean.y);
C[1, 0] += (point.y - mean.y) * (point.x - mean.x);
C[1, 1] += (point.y - mean.y) * (point.y - mean.y);
}
C[0, 0] /= W;
C[0, 1] /= W;
C[1, 0] /= W;
C[1, 1] /= W;
Matrix2d CM = new Matrix2d(C);
SVD svd = new SVD(C);
//svd.w - eigenvalue, start from 1
//svd.u - eigenvector, start from 1
int max = 1, min = 2;
if (svd.w[max] < svd.w[min])
{
int temp = max;
max = min;
min = temp;
}
float major = 2 * Mathf.Sqrt(svd.w[max]);
Vector2 majoraxis = new Vector2(svd.u[1, max], svd.u[2, max]);
majoraxis.Normalize();
float minor = 2 * Mathf.Sqrt(svd.w[min]);
Vector2 minoraxis = new Vector2(svd.u[1, min], svd.u[2, min]);
minoraxis.Normalize();
majorendp = mean + majoraxis * major;
majorstartp = mean - majoraxis * major;
minorendp = mean + minoraxis * minor;
minorstartp = mean - minoraxis * minor;
double error = Mathf.Abs(W - 4 * Mathf.PI * Mathf.Sqrt(CM.Det()));
error /= W;
if (!m_engine.m_is_quiet)
{
Debug.Log("Like a ellipse error: " + error); //10^-2 may be a good threshold
}
return(error);
}
