hessian-matrix-det

hessian_matrix_det

skimage.feature.hessian_matrix_det(image, sigma) [source]

Computes the approximate Hessian Determinant over an image.

This method uses box filters over integral images to compute the approximate Hessian Determinant as described in [R151].

Parameters:	image : array The image over which to compute Hessian Determinant. sigma : float Standard deviation used for the Gaussian kernel, used for the Hessian matrix.
Returns:	out : array The array of the Determinant of Hessians.

Notes

The running time of this method only depends on size of the image. It is independent of sigma as one would expect. The downside is that the result for sigma less than 3 is not accurate, i.e., not similar to the result obtained if someone computed the Hessian and took it’s determinant.

References

[R151]

(1, 2) Herbert Bay, Andreas Ess, Tinne Tuytelaars, Luc Van Gool, “SURF: Speeded Up Robust Features” ftp://ftp.vision.ee.ethz.ch/publications/articles/eth_biwi_00517.pdf