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1 Machine Graphics and Vision

1 2002

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Exploiting color and topological features for region segmentation with recursive fuzzy C-means

Cucchiara R., Grana C., Seidenari S., Pellacani G.

Machine Graphics and Vision

2002

Vol. 11, No. 2/3

169-182

In this paper we define a novel approach to images segmentation into regions which focuses on both visual and topologocal cues, namely color similarity, inclusion and spatial adjacency. Many color clustering algorithms have been proposed in the past for skin lesion images but mone exploits explicity the inclusion properties between regions. Our algorithm is based on a recursive version of fuzzy c-means (FCM) clustering algorithm in the 2D color histogram constructed by Principal Component Analysis (PCA) of the color space. The distinctive feature of the proposal is that recursion is guided by evaluation of adjacency and mutual inclusion properties of extracted regions; then, the recursive analysis addresses only included or regions with a non-negligible size. This approach allows a coarse-to-fine segmentation which focuses attention on the inner parts of the images, in order to highlight the internal structure of the object depiced in the image. This could be particulary useful in many applications, especially in biomedical image analysis. Inthis work we apply the technique to segmentation of skin lesions in dermatoscopic images. It could be a suitable support for diagnosis of skin melanoma, since dermatologists are interrested in analysis of spatial relations, symmetrical positions and inlusion of regions.