Fingerprint image segmentation using modified fuzzy c-means algorithm

Jia-Yin Kang; Cheng-Long Gong; Wen-Juan Zhang

doi:10.4236/jbise.2009.28096

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Journal of Biomedical Science and Engine... > Vol.2 No.8, December 2009

Fingerprint image segmentation using modified fuzzy c-means algorithm ()

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

DOI: 10.4236/jbise.2009.28096 PDF HTML 6,277 Downloads 12,283 Views Citations

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.

Keywords

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

Share and Cite:

Kang, J. , Gong, C. and Zhang, W. (2009) Fingerprint image segmentation using modified fuzzy c-means algorithm. Journal of Biomedical Science and Engineering, 2, 656-660. doi: 10.4236/jbise.2009.28096.

Conflicts of Interest

The authors declare no conflicts of interest.

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