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SOM and fuzzy based color image segmentation

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Abstract

Spatial information enhances the quality of clustering which is not utilized in the conventional FCM. Normally fuzzy c-mean (FCM) algorithm is not used for color image segmentation and also it is not robust against noise. In this paper, we presented a modified version of fuzzy c-means (FCM) algorithm that incorporates spatial information into the membership function for clustering of color images A progressive technique based on SOM is used to automatically find the number of optimal clusters. The results show that our technique outperforms state-of-the art methods.

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Acknowledgement

This work (2011-0015740) was supported by Mid-career Researcher Program through NRF grant funded by the MEST.

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Authors and Affiliations

  1. National University of Computer & Emerging Sciences, Islamabad, Pakistan

    Ahmad Khan & M. Arfan Jaffar

  2. Gwangju Institute of Science & Technology, Gwangju, Korea

    M. Arfan Jaffar & Tae-Sun Choi

Authors
  1. Ahmad Khan
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  2. M. Arfan Jaffar
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  3. Tae-Sun Choi
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Correspondence to M. Arfan Jaffar.

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Khan, A., Jaffar, M.A. & Choi, TS. SOM and fuzzy based color image segmentation. Multimed Tools Appl 64, 331–344 (2013). https://doi.org/10.1007/s11042-012-1003-6

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  • DOI: https://doi.org/10.1007/s11042-012-1003-6

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