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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 683494, 11 pages
Research Article

A Fast Iterative Pursuit Algorithm in Robust Face Recognition Based on Sparse Representation

1School of Information Science and Technology, Northwest University, Xi’an 710069, China
2Department of Mathematics, Northwest University, Xi’an 710069, China

Received 3 October 2013; Revised 19 December 2013; Accepted 28 December 2013; Published 13 February 2014

Academic Editor: Chung-Hao Chen

Copyright © 2014 Zhao Jian 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.


A relatively fast pursuit algorithm in face recognition is proposed, compared to existing pursuit algorithms. More stopping rules have been put forward to solve the problem of slow response of OMP, which can fully develop the superiority of pursuit algorithm—avoiding to process useless information in the training dictionary. For the test samples that are affected by partial occlusion, corruption, and facial disguise, recognition rates of most algorithms fall rapidly. The robust version of this algorithm can identify these samples automatically and process them accordingly. The recognition rates on ORL database, Yale database, and FERET database are 95.5%, 93.87%, and 92.29%, respectively. The recognition performance under various levels of occlusion and corruption is also experimentally proved to be significantly enhanced.