hessian_matrix_eigvals(H_elems)

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).

Compute Eigenvalues of Hessian matrix.

Examples

This example is valid syntax, but we were not able to check execution

>>> 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')
... 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.]])

See :

Back References

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skimage.feature.corner.hessian_matrix_eigvals

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