`skimage.filters.edges:scharr`

source: /dev/scikit-image/src/skimage/filters/edges.py:316

Signature

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

Summary

Find the edge magnitude using the Scharr 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

sch_mag = np.sqrt(sum([scharr(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 Scharr edge map.

Notes

The Scharr operator has a better rotation invariance than other edge filters such as the Sobel or the Prewitt operators.

Examples

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

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Aliases

skimage.filters.scharr