/// <summary>
/// Extracts corners from the gradient image. The method used here is one which uses the eigensystem at each
/// pixel (computed from the smoothed second moments) to determine whether a corner is present. A corner is
/// one in which both eigenvalues are above the threshold.
/// </summary>
/// <param name="grad">Gradient image of source</param>
/// <param name="threshold">Threshold used to determine corners</param>
/// <returns>A list of corners</returns>
public static unsafe Vector[] Extract(GradientImage grad, float threshold)
{
EigensystemImage eigen = EigensystemImage.Compute(SecondMomentImage.Compute(grad));
List <Vector> points = new List <Vector>();
int rows = eigen.Rows;
int columns = eigen.Columns;
fixed(float *src = eigen.RawArray)
{
float *srcPtr = src;
int channels = eigen.Channels;
for (int r = 0; r < rows; r++)
{
for (int c = 0; c < columns; c++, srcPtr += channels)
{
float lambda1 = srcPtr[0];
float lambda2 = srcPtr[1];
if (lambda1 > threshold && lambda2 > threshold)
{
points.Add(new DenseVector(new float[] { c, r }));
}
}
}
}
return(points.ToArray());
}
/// <summary>
/// Computes the eigensystem image from the second moment image provided.
/// </summary>
/// <param name="moments">Contains the second moments used to compute the eigensystem image.</param>
/// <param name="sigma">The sigma to use when convolving the second moment image</param>
/// <returns>the eigensystem image</returns>
public static unsafe EigensystemImage Compute(SecondMomentImage moments, float sigma)
{
moments = Convolution.ConvolveGaussian <SecondMomentImage>(moments, sigma);
int rows = moments.Rows;
int columns = moments.Columns;
float[, ,] data = new float[rows, columns, 6];
fixed(float *src = moments.RawArray, dst = data)
{
float *srcPtr = src;
float *dstPtr = dst;
int length = rows * columns;
while (length-- > 0)
{
float a11 = *srcPtr++;
float a22 = *srcPtr++;
float a12 = *srcPtr++;
float a21 = a12;
float sqrt = (float)Math.Sqrt(4 * a12 * a21 + Math.Pow(a11 - a22, 2));
float sum = a11 + a22;
float eigen1 = sum + sqrt;
float eigen2 = sum - sqrt;
float x1, y1;
findEigenvector(a11, a12, a21, a22, eigen1, out x1, out y1);
float x2, y2;
findEigenvector(a11, a12, a21, a22, eigen2, out x2, out y2);
*dstPtr++ = eigen1;
*dstPtr++ = eigen2;
*dstPtr++ = x1;
*dstPtr++ = y1;
*dstPtr++ = x2;
*dstPtr++ = y2;
}
}
EigensystemImage image = new EigensystemImage();
image.SetData(data);
return(image);
}