Image segmentation by means of complex networks centrality indices

Fenu C.
2021-01-01

Abstract

In this paper, we propose a novel approach to perform multi-label segmentation. Starting from an image, we construct the associated weighted graph and assign to a small number of pixels (seeds) a label. The aim is to assign each unlabeled pixel to a label in order to identify different regions. Our algorithm uses the notion of communicability from complex networks theory to compute the easiness for an unlabeled pixel to reach a labeled one. By assigning each pixel to the label for which the greatest communicability is calculated, we can perform good image segmentation.
2021
978-1-6654-5843-6
centrality indices
complex networks
image segmentation
medical imaging
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