PMID: 16519361Mar 8, 2006Paper

A new algorithm for distorted fingerprints matching based on normalized fuzzy similarity measure

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Xinjian ChenXin Yang

Abstract

Coping with nonlinear distortions in fingerprint matching is a challenging task. This paper proposes a novel algorithm, normalized fuzzy similarity measure (NFSM), to deal with the nonlinear distortions. The proposed algorithm has two main steps. First, the template and input fingerprints were aligned. In this process, the local topological structure matching was introduced to improve the robustness of global alignment. Second, the method NFSM was introduced to compute the similarity between the template and input fingerprints. The proposed algorithm was evaluated on fingerprints databases of FVC2004. Experimental results confirm that NFSM is a reliable and effective algorithm for fingerprint matching with nonliner distortions. The algorithm gives considerably higher matching scores compared to conventional matching algorithms for the deformed fingerprints.

References

Feb 8, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·A K JainS Pankanti
Jan 1, 1995·IEEE Transactions on Neural Networks·S Hashem, B Schmeiser

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Citations

May 5, 2012·PloS One·Xunqiang TaoJie Tian
Dec 14, 2011·IEEE Transactions on Pattern Analysis and Machine Intelligence·Jifeng DaiJie Zhou
Sep 10, 2015·IEEE Transactions on Pattern Analysis and Machine Intelligence·Xuanbin SiYuxuan Luo
Aug 24, 2013·IEEE Transactions on Pattern Analysis and Machine Intelligence·Eryun LiuJie Tian
Nov 20, 2010·IEEE Transactions on Pattern Analysis and Machine Intelligence·Anil K Jain, Jianjiang Feng
Apr 18, 2009·IEEE Transactions on Pattern Analysis and Machine Intelligence·Anil K Jain, Jianjiang Feng
Jun 28, 2012·Sensors·Miguel Angel Medina-PérezLeopoldo Altamirano-Robles

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