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L. Szilagyi, Z. Benyo and S. M. Szilagyii. (2003) MR brain image segmentation using an enhanced fuzzy c- means algorithm. 25th Annual International Conference of IEEE EMBS, 17–21.

has been cited by the following article:

• TITLE: Fingerprint image segmentation using modified fuzzy c-means algorithm

  AUTHORS: Jia-Yin Kang, Cheng-Long Gong, Wen-Juan Zhang

  KEYWORDS: Fingerprint; Segmentation; Fuzzy C-means; Histogram; Robustness

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.2 No.8, December 15, 2009

  ABSTRACT: Fingerprint segmentation is a crucial step in fingerprint recognition system, and determines the results of fingerprint analysis and recognition. This paper proposes an efficient approach for fingerprint segmentation based on modified fuzzy c-means (FCM). The proposed method is realized by modifying the objective function in the Szilagyi’s algorithm via introducing histogram-based weight. Experimental results show that the proposed approach has an efficient performance while segmenting both original fingerprint image and fingerprint images corrupted by different type of noises.