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Color Image Segmentation Using Anisotropic Diffusion and Agglomerative Hierarchical Clustering

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Advances in Multimedia Information Processing — PCM 2002 (PCM 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2532))

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Abstract

A new color image segmentation scheme is presented in this paper. The proposed algorithm consists of image simplification, region labeling and color clustering. The vector-valued diffusion process is performed in the perceptually uniform LUV color space. We present a discrete 3-D diffusion model for easy implementation. The statistical characteristics of each labeled region are employed to estimate the number of total clusters and agglomerative hierarchical clustering is performed with the estimated number of clusters. Since the proposed clustering algorithm counts each region as a unit, it does not generate oversegmentation along region boundaries.

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© 2002 Springer-Verlag Berlin Heidelberg

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Kim, D., Yo-Sung, H., Manjunath, B.S. (2002). Color Image Segmentation Using Anisotropic Diffusion and Agglomerative Hierarchical Clustering. In: Chen, YC., Chang, LW., Hsu, CT. (eds) Advances in Multimedia Information Processing — PCM 2002. PCM 2002. Lecture Notes in Computer Science, vol 2532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36228-2_94

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  • DOI: https://doi.org/10.1007/3-540-36228-2_94

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00262-8

  • Online ISBN: 978-3-540-36228-9

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