Document

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

Notes

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

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 :None:None:`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.

Find the edge magnitude using the Scharr transform.

Examples

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

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

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

skimage.filters.edges.roberts skimage.filters.edges.scharr skimage.filters.edges.sobel skimage.filters.edges.prewitt

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them