Parallel computing-based sclera recognition for human identification

Yong Lin; Eliza Y. Du; Zhi Zhou

doi:10.1117/12.918166

8 May 2012 Parallel computing-based sclera recognition for human identification

Yong Lin, Eliza Y. Du, Zhi Zhou

Proceedings Volume 8406, Mobile Multimedia/Image Processing, Security, and Applications 2012; 840603 (2012) https://doi.org/10.1117/12.918166
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

Compared to iris recognition, sclera recognition which uses line descriptor can achieve comparable recognition accuracy in visible wavelengths. However, this method is too time-consuming to be implemented in a real-time system. In this paper, we propose a GPU-based parallel computing approach to reduce the sclera recognition time. We define a new descriptor in which the information of KD tree structure and sclera edge are added. Registration and matching task is divided into subtasks in various sizes according to their computation complexities. Every affine transform parameters are generated by searching on KD tree. Texture memory, constant memory, and shared memory are used to store templates and transform matrixes. The experiment results show that the proposed method executed on GPU can dramatically improve the sclera matching speed in hundreds of times without accuracy decreasing.

Citation Download Citation

Yong Lin, Eliza Y. Du, and Zhi Zhou "Parallel computing-based sclera recognition for human identification", Proc. SPIE 8406, Mobile Multimedia/Image Processing, Security, and Applications 2012, 840603 (8 May 2012); https://doi.org/10.1117/12.918166

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KEYWORDS

Sclera

Image segmentation

Detection and tracking algorithms

Iris recognition

Algorithm development

Databases

Image registration

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