bundles / skimage 0.26.1rc0.dev0 / skimage / feature / corner / hessian_matrix_eigvals

function

`skimage.feature.corner:hessian_matrix_eigvals`

source: /_skimage2/feature/corner.py:488

Signature

def hessian_matrix_eigvals(H_elems)

Summary

Compute eigenvalues of Hessian matrix.

Parameters

H_elems : list of ndarray: The upper-diagonal elements of the Hessian matrix, as returned by hessian_matrix.

Returns

eigs : ndarray: The eigenvalues of the Hessian matrix, in decreasing order. The eigenvalues are the leading dimension. That is, eigs[i, j, k] contains the ith-largest eigenvalue at position (j, k).

Examples

from skimage.feature import hessian_matrix, hessian_matrix_eigvals
square = np.zeros((5, 5))
square[2, 2] = 4
H_elems = hessian_matrix(square, sigma=0.1, order='rc',
                         use_gaussian_derivatives=False)
hessian_matrix_eigvals(H_elems)[0]

✓

array([[ 0.,  0.,  2.,  0.,  0.],
       [ 0.,  1.,  0.,  1.,  0.],
       [ 2.,  0., -2.,  0.,  2.],
       [ 0.,  1.,  0.,  1.,  0.],
       [ 0.,  0.,  2.,  0.,  0.]])

Aliases

skimage.feature.hessian_matrix_eigvals