Hands-On Image Processing with Python

RAG merging

In this section, we discuss how the Region Adjacency Graph (RAG) can be used to combine the over-segmented regions of an image, to obtain a better segmentation. It uses the SLIC algorithm to first segment the input image and obtain the region labels. Then, it constructs a RAG and progressively merges the over-segmented regions that are similar in color. Merging two adjacent regions produces a new region with all the pixels from the merged regions. Regions are merged until no highly similar region pairs remain:

from skimage import segmentationfrom skimage.future import graphdef _weight_mean_color(graph, src, dst, n): diff = graph.node[dst]['mean color'] - graph.node[n]['mean color'] diff = np.linalg.norm(diff) return {'weight': ...