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bundles / skimage latest / skimage / feature / corner / corner_harris

function

skimage.feature.corner:corner_harris

source: /dev/scikit-image/src/skimage/feature/corner.py:653

Signature

def corner_harris(image, method = k, k = 0.05, eps = 1e-06, sigma = 1)

Summary

Compute Harris corner measure response image.

Extended Summary

This corner detector uses information from the auto-correlation matrix A 

A = [(imx**2)   (imx*imy)] = [Axx Axy]
    [(imx*imy)   (imy**2)]   [Axy Ayy]

Where imx and imy are first derivatives, averaged with a gaussian filter. The corner measure is then defined as 

det(A) - k * trace(A)**2

or 

2 * det(A) / (trace(A) + eps)

Parameters

image : ndarray of shape (M, N)

Input image.

method : {'k', 'eps'}, optional

Method to compute the response image from the auto-correlation matrix.

k : float, optional

Sensitivity factor to separate corners from edges, typically in range [0, 0.2]. Small values of k result in detection of sharp corners.

eps : float, optional

Normalisation factor (Noble's corner measure).

sigma : float, optional

Standard deviation used for the Gaussian kernel, which is used as weighting function for the auto-correlation matrix.

Returns

response : ndarray

Harris response image.

Examples

from skimage.feature import corner_harris, corner_peaks
square = np.zeros([10, 10])
square[2:8, 2:8] = 1
square.astype(int)
corner_peaks(corner_harris(square), min_distance=1)
✓

Aliases

  • skimage.feature.corner_harris

Referenced by

This package