Open AccessFingerprint image segmentation using modified fuzzy c-means algorithm
Author(s) -
Jiayin Kang,
Chenglong Gong,
Wenjuan Zhang
Publication year - 2009
Publication title -
journal of biomedical science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1937-688X
pISSN - 1937-6871
DOI - 10.4236/jbise.2009.28096
Subject(s) - fingerprint (computing) , artificial intelligence , pattern recognition (psychology) , computer science , histogram , fingerprint recognition , segmentation , fuzzy logic , computer vision , image segmentation , image (mathematics)
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