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

Notes

The edge magnitude depends slightly on edge directions, since the approximation of the gradient operator by the Prewitt operator is not completely rotation invariant. For a better rotation invariance, the Scharr operator should be used. The Sobel operator has a better rotation invariance than the Prewitt operator, but a worse rotation invariance than the Scharr operator.

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:

prw_mag = np.sqrt(sum([prewitt(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 Prewitt edge map.

Find the edge magnitude using the Prewitt 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.prewitt(camera)

See :

Back References

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

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

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