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The Scientific World Journal
Volume 2014, Article ID 157173, 19 pages
http://dx.doi.org/10.1155/2014/157173
Research Article

Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion

1College of Computer Science and Technology, Jilin University, Changchun 130012, China
2Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
3College of Software, Nanchang Hangkong University, Nanchang 330063, China
4Internet of Things Technology Institute, Nanchang Hangkong University, Nanchang 330063, China

Received 19 August 2013; Accepted 10 November 2013; Published 10 February 2014

Academic Editors: O. Greevy and S.-S. Liaw

Copyright © 2014 Ying Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Ying Chen, Yuanning Liu, Xiaodong Zhu, Fei He, Hongye Wang, and Ning Deng, “Efficient Iris Recognition Based on Optimal Subfeature Selection and Weighted Subregion Fusion,” The Scientific World Journal, vol. 2014, Article ID 157173, 19 pages, 2014. https://doi.org/10.1155/2014/157173.