Extending the Capture Volume of an Iris Recognition System Using Wavefront Coding and Super-Resolution

Sheng Hsun Hsieh, Yung Hui Li, Chung-Hao Tien, Chin Chen Chang

研究成果: Article同行評審

17 引文 斯高帕斯(Scopus)

摘要

Iris recognition has gained increasing popularity over the last few decades; however, the stand-off distance in a conventional iris recognition system is too short, which limits its application. In this paper, we propose a novel hardware-software hybrid method to increase the stand-off distance in an iris recognition system. When designing the system hardware, we use an optimized wavefront coding technique to extend the depth of field. To compensate for the blurring of the image caused by wavefront coding, on the software side, the proposed system uses a local patch-based super-resolution method to restore the blurred image to its clear version. The collaborative effect of the new hardware design and software post-processing showed great potential in our experiment. The experimental results showed that such improvement cannot be achieved by using a hardware-or software-only design. The proposed system can increase the capture volume of a conventional iris recognition system by three times and maintain the system's high recognition rate.

原文English
頁(從 - 到)3342-3350
頁數9
期刊IEEE Transactions on Cybernetics
46
發行號12
DOIs
出版狀態Published - 1 12月 2016

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