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

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)3342-3350
Number of pages9
JournalIEEE Transactions on Cybernetics
Volume46
Issue number12
DOIs
StatePublished - 1 Dec 2016

Keywords

  • Extended depth of field (EDoF)
  • image fusion
  • iris recognition
  • super-resolution

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