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Proceedings Paper

Feature quality-based multimodal unconstrained eye recognition
Author(s): Zhi Zhou; Eliza Y. Du; Yong Lin; N. Luke Thomas; Craig Belcher; Edward J. Delp
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Paper Abstract

Iris recognition has been tested to the most accurate biometrics using high resolution near infrared images. However, it does not work well under visible wavelength illumination. Sclera recognition, however, has been shown to achieve reasonable recognition accuracy under visible wavelengths. Combining iris and sclera recognition together can achieve better recognition accuracy. However, image quality can significantly affect the recognition accuracy. Moreover, in unconstrained situations, the acquired eye images may not be frontally facing. In this research, we proposed a feature quality-based multimodal unconstrained eye recognition method that combine the respective strengths of iris recognition and sclera recognition for human identification and can work with frontal and off-angle eye images. The research results show that the proposed method is very promising.

Paper Details

Date Published: 28 May 2013
PDF: 14 pages
Proc. SPIE 8755, Mobile Multimedia/Image Processing, Security, and Applications 2013, 87550J (28 May 2013); doi: 10.1117/12.2018664
Show Author Affiliations
Zhi Zhou, Indiana Univ.-Purdue Univ. Indianapolis (United States)
Eliza Y. Du, Indiana Univ.-Purdue Univ. Indianapolis (United States)
Yong Lin, Indiana Univ.-Purdue Univ. Indianapolis (United States)
Xidian Univ. (China)
N. Luke Thomas, Indiana Univ.-Purdue Univ. Indianapolis (United States)
Craig Belcher, Indiana Univ.-Purdue Univ. Indianapolis (United States)
Edward J. Delp, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 8755:
Mobile Multimedia/Image Processing, Security, and Applications 2013
Sos S. Agaian; Sabah A. Jassim; Eliza Yingzi Du, Editor(s)

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