`skimage.graph._rag:rag_boundary`

source: /_skimage2/graph/_rag.py:402

Signature

def rag_boundary(labels, edge_map, connectivity = 2)

Summary

Comouter RAG based on region boundaries

Extended Summary

Given an image's initial segmentation and its edge map this method constructs the corresponding Region Adjacency Graph (RAG). Each node in the RAG represents a set of pixels within the image with the same label in labels. The weight between two adjacent regions is the average value in edge_map along their boundary.

labels: The labelled image.
edge_map: This should have the same shape as that of labels. For all pixels along the boundary between 2 adjacent regions, the average value of the corresponding pixels in edge_map is the edge weight between them.
connectivity: Pixels with a squared distance less than connectivity from each other are considered adjacent. It can range from 1 to labels.ndim. Its behavior is the same as connectivity parameter in scipy.ndimage.generate_binary_structure.

Examples

from skimage import data, segmentation, filters, color, graph
img = data.chelsea()
labels = segmentation.slic(img)
edge_map = filters.sobel(color.rgb2gray(img))
rag = graph.rag_boundary(labels, edge_map)

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Aliases

skimage.graph.rag_boundary