Binary image segmentation using weighted skeletons
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When one starts to learn mathematical morphology, binary morphology techniques generally appear early on the menu. they are often viewed as somewhat more basic than, and a good introduction to, more complicated items used in gray-level morphology. However, mathematical morphology, being based on topology, is very deeply rooted in the binary world, which is more full of surprise than one would think. Segmenting overlapping convex particles in binary images, which means separating them from each other, is one of the older problems in binary morphology. It has often been investigated in past works in very different contexts, using such tools as ultimate erosions, skeletons, conditional bisectors, and reconstruction by watershed lines, to name a few. Although well suited to a large number of applications, these techniques often lead to oversegmentation when there is a wide range in the dimension of the overlapping particles. In this paper we present a new method to overcome this problem based on the concept of weighted skeletons. We will apply it to a real-world problem: the separation of man-made vitreous fibers embedded in resin, for which it was originally developed. The first section refreshes our memory on the fundamental tools that will be used in the second section, where we present some binary segmentation methods based on ultimate erosions and related problems. The third section presents our proposed method and its results.
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