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Iris recognition based on robust principal component analysis

[+] Author Affiliations
Pradeep Karn

Sichuan University, Image Information Institute, College of Electronics and Information Engineering, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China

Xiao Hai He

Sichuan University, Image Information Institute, College of Electronics and Information Engineering, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China

Shuai Yang

Sichuan University, Image Information Institute, College of Electronics and Information Engineering, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China

Xiao Hong Wu

Sichuan University, Image Information Institute, College of Electronics and Information Engineering, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China

J. Electron. Imaging. 23(6), 063002 (Nov 03, 2014). doi:10.1117/1.JEI.23.6.063002
History: Received June 20, 2014; Revised September 27, 2014; Accepted October 1, 2014
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Abstract.  Iris images acquired under different conditions often suffer from blur, occlusion due to eyelids and eyelashes, specular reflection, and other artifacts. Existing iris recognition systems do not perform well on these types of images. To overcome these problems, we propose an iris recognition method based on robust principal component analysis. The proposed method decomposes all training images into a low-rank matrix and a sparse error matrix, where the low-rank matrix is used for feature extraction. The sparsity concentration index approach is then applied to validate the recognition result. Experimental results using CASIA V4 and IIT Delhi V1iris image databases showed that the proposed method achieved competitive performances in both recognition accuracy and computational efficiency.

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Citation

Pradeep Karn ; Xiao Hai He ; Shuai Yang and Xiao Hong Wu
"Iris recognition based on robust principal component analysis", J. Electron. Imaging. 23(6), 063002 (Nov 03, 2014). ; http://dx.doi.org/10.1117/1.JEI.23.6.063002


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Video-based noncooperative iris image segmentation. IEEE Trans Syst Man Cybern B Cybern 2011;41(1):64-74.
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