Abstract

In this paper, we propose a novel clustering algorithm based on Fuzzy C-Means (FCM) and Speeded-Up Robust Feature (SURF) for multispectral image segmentation. In the experiments, color images and multispectral images from IRIS Lab data base, which consists of face images taken along the visible spectrum, have been used to illustrate the performances of the proposed algorithm and to compare its outputs with other algorithms. Results demonstrate that the proposed method outperforms other clustering methods in segmenting color images as well as multispectral images.

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