skimage2.feature.hessian_matrix_det#
- skimage2.feature.hessian_matrix_det(image, sigma=1, approximate=True)[source]#
Compute the approximate Hessian Determinant over an image.
The 2D approximate method uses box filters over integral images to compute the approximate Hessian Determinant.
- Parameters:
- imagendarray
The image over which to compute the Hessian Determinant.
- sigmafloat, optional
Standard deviation of the Gaussian kernel used for the Hessian matrix.
- approximatebool, optional
If
Trueand the image is 2D, use a much faster approximate computation. This argument has no effect on 3D and higher images.
- Returns:
- outarray
The array of the Determinant of Hessians.
Notes
For 2D images when
approximate=True, the running time of this method only depends on size of the image. It is independent ofsigmaas one would expect. The downside is that the result forsigmaless than3is not accurate, i.e., not similar to the result obtained if someone computed the Hessian and took its determinant.References
[1]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
