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Proceedings Paper

A novel fingerprint recognition algorithm based on VK-LLE
Author(s): Jing Luo; Shu-zhong Lin; Jian-yun Ni; Li-mei Song
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Paper Abstract

It is a challenging problem to overcome shift and rotation and nonlinearity in fingerprint images. By analyzing the shortcoming of fingerprint recognition algorithm on shift or rotation images at present, manifold learning algorithm is introduced. A fingerprint recognition algorithm has been proposed based on locally linear embedding of variable neighbourhood k (VK-LLE). Firstly, approximate geodesic distance between any two points is computed by ISOMAP ( isometric feature mapping) and then the neighborhood is determined for each point by the relationship between its local estimated geodesic distance matrix and local Euclidean distance matrix. Secondly, the dimension of fingerprint image is reduced by nonlinear dimension-reduction method. And the best projected features of original fingerprint data of large dimension are acquired. By analyzing the changes of recognition accuracy with the neighborhood and embedding dimension, the neighborhood and embedding dimension is determined at last. Finally, fingerprint recognition is accomplished by Euclidean distance Classifier. The experimental results based on standard fingerprint datasets have verified the proposed algorithm had a better robustness to those fingerprint images of shift or rotation or nonlinearity than the algorithm using LLE, thus this method has some values in practice.

Paper Details

Date Published: 10 July 2009
PDF: 6 pages
Proc. SPIE 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, 748910 (10 July 2009); doi: 10.1117/12.836795
Show Author Affiliations
Jing Luo, Tianjin Polytechnic Univ. (China)
Shu-zhong Lin, Tianjin Polytechnic Univ. (China)
Jian-yun Ni, Tianjin Univ. of Technology (China)
Li-mei Song, Tianjin Polytechnic Univ. (China)

Published in SPIE Proceedings Vol. 7489:
PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering
Honghua Tan; Qi Luo, Editor(s)

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