skimage 0.17.2

ParametersReturnsBackRef
perimeter(image, neighbourhood=4)

Parameters

image : (N, M) ndarray

2D binary image.

neighbourhood : 4 or 8, optional

Neighborhood connectivity for border pixel determination. It is used to compute the contour. A higher neighbourhood widens the border on which the perimeter is computed.

Returns

perimeter : float

Total perimeter of all objects in binary image.

Calculate total perimeter of all objects in binary image.

Examples

This example is valid syntax, but we were not able to check execution
>>> from skimage import data, util
... from skimage.measure import label
... # coins image (binary)
... img_coins = data.coins() > 110
... # total perimeter of all objects in the image
... perimeter(img_coins, neighbourhood=4) # doctest: +ELLIPSIS 7796.867...
This example is valid syntax, but we were not able to check execution
>>> perimeter(img_coins, neighbourhood=8)  # doctest: +ELLIPSIS
8806.268...
See :

Back References

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

skimage.measure._regionprops.perimeter

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


File: /skimage/measure/_regionprops.py#899
type: <class 'function'>
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