`skimage.filters.edges:farid`

source: /dev/scikit-image/src/skimage/filters/edges.py :718

Signature

   def     farid (    image    ,    mask    =  None   ,  * ,     axis    =  None   ,    mode    =  reflect   ,    cval    =  0.0     )

Summary

Find the edge magnitude using the Farid transform.

Parameters

image : array

The input image.

mask : array of bool, optional

Clip the output image to this mask. (Values where mask=0 will be set to 0.)

axis : int or sequence of int, optional

Compute the edge filter along this axis. If not provided, the edge magnitude is computed. This is defined as

farid_mag = np.sqrt(sum([farid(image, axis=i)**2
                         for i in range(image.ndim)]) / image.ndim)

The magnitude is also computed if axis is a sequence.

mode : str or sequence of str, optional

The boundary mode for the convolution. See scipy.ndimage.convolve for a description of the modes. This can be either a single boundary mode or one boundary mode per axis.

cval : float, optional

When mode is 'constant', this is the constant used in values outside the boundary of the image data.

Returns

output : array of float: The Farid edge map.

Notes

Take the square root of the sum of the squares of the horizontal and vertical derivatives to get a magnitude that is somewhat insensitive to direction. Similar to the Scharr operator, this operator is designed with a rotation invariance constraint.

Examples

from skimage import data
camera = data.camera()
from skimage import filters
edges = filters.farid(camera)

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Aliases

skimage.filters.farid

Referenced by

This package

release_notes:release_0.16