Region Boundary based RAGs¶

Construct a region boundary RAG with the rag_boundary function. The function skimage.future.graph.rag_boundary() takes an edge_map argument, which gives the significance of a feature (such as edges) being present at each pixel. In a region boundary RAG, the edge weight between two regions is the average value of the corresponding pixels in edge_map along their shared boundary.

from skimage.future import graph
from skimage import data, segmentation, color, filters, io
from matplotlib import pyplot as plt


img = data.coffee()
gimg = color.rgb2gray(img)

labels = segmentation.slic(img, compactness=30, n_segments=400)
edges = filters.sobel(gimg)
edges_rgb = color.gray2rgb(edges)

g = graph.rag_boundary(labels, edges)
lc = graph.show_rag(labels, g, edges_rgb, img_cmap=None, edge_cmap='viridis',
                    edge_width=1.2)

plt.colorbar(lc, fraction=0.03)
io.show()

Total running time of the script: ( 0 minutes 0.664 seconds)

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