A novel matching technique for fingerprint recognition by graphical structures

Fingerprint matching is an important issue in automatic fingerprint identification systems. There are difficulties about fingerprint matching based on neighborhood. One is the size of the neighborhood can not be determined readily, the other is the feature in the neighborhood can be affected by the noise. To deal with these problem, we developed a novel algorithm for fingerprint matching based on local structures to efficiently extract neighboring minutiae features. Neighboring features present the information of peripheral minutiae which directly connect with the central minutiae on topology. We use one feature vector to present neighboring features from different samples. The samples considered as the same class can make the proposed algorithm robust to rotation and translation of fingerprint images. The experiments are conducted on FVC2002, and the results illustrate the effectiveness of the proposed algorithm.

[1]  Mohamed Aissani,et al.  Fingerprint matching from minutiae texture maps , 2007, Pattern Recognit..

[2]  Sharath Pankanti,et al.  On the Individuality of Fingerprints , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Pauli Kuosmanen,et al.  Fingerprint Matching Using an Orientation-Based Minutia Descriptor , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Zsolt Miklós Kovács-Vajna,et al.  A Fingerprint Verification System Based on Triangular Matching and Dynamic Time Warping , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Anil K. Jain,et al.  Fingerprint Quality Indices for Predicting Authentication Performance , 2005, AVBPA.

[6]  Gaurav Garg,et al.  Fast and Accurate Fingerprint Verification , 2001, AVBPA.

[7]  Fang-Hsuan Cheng,et al.  Fast algorithm for point pattern matching: Invariant to translations, rotations and scale changes , 1997, Pattern Recognit..

[8]  Eric Backer,et al.  Finding point correspondences using simulated annealing , 1995, Pattern Recognit..

[9]  Sandip Das,et al.  Simple algorithms for partial point set pattern matching under rigid motion , 2006, Pattern Recognit..

[10]  Tu Van Le,et al.  A fingerprint recognizer using fuzzy evolutionary programming , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[11]  Davide Maltoni,et al.  Minutia Cylinder-Code: A New Representation and Matching Technique for Fingerprint Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Yilong Yin,et al.  A Fingerprint Matching Algorithm Based On Delaunay Triangulation Net , 2005, The Fifth International Conference on Computer and Information Technology (CIT'05).

[13]  Yi Chen,et al.  Pores and Ridges: High-Resolution Fingerprint Matching Using Level 3 Features , 2007 .

[14]  Loris Nanni,et al.  Two-class fingerprint matcher , 2006, Pattern Recognit..

[15]  Bir Bhanu,et al.  Fingerprint matching by genetic algorithms , 2006, Pattern Recognit..

[16]  D. M. Weber,et al.  A cost effective fingerprint verification algorithm for commercial applications , 1992, Proceedings of the 1992 South African Symposium on Communications and Signal Processing.