An Embedded Iris Recognition System Optimization using Dynamically ReconfigurableDecoder with LDPC Codes

• URL: http://arxiv.org/abs/2107.03688v1
• Date: Thu, 8 Jul 2021 09:04:11 GMT
• Title: An Embedded Iris Recognition System Optimization using Dynamically ReconfigurableDecoder with LDPC Codes
• Authors: Longyu Ma, Chiu-Wing Sham, Chun Yan Lo, and Xinchao Zhong
• Abstract summary: The proposed design includes a minimal set of computer vision modules and multi-mode QC-LDPC decoder. We show that we can apply Dynamic Partial Reconfiguration technology to implement the multi-mode QC-LDPC decoder for the iris recognition system.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Extracting and analyzing iris textures for biometric recognition has been extensively studied. As the transition of iris recognition from lab technology to nation-scale applications, most systems are facing high complexity in either time or space, leading to unfitness for embedded devices. In this paper, the proposed design includes a minimal set of computer vision modules and multi-mode QC-LDPC decoder which can alleviate variability and noise caused by iris acquisition and follow-up process. Several classes of QC-LDPC code from IEEE 802.16 are tested for the validity of accuracy improvement. Some of the codes mentioned above are used for further QC-LDPC decoder quantization, validation and comparison to each other. We show that we can apply Dynamic Partial Reconfiguration technology to implement the multi-mode QC-LDPC decoder for the iris recognition system. The results show that the implementation is power-efficient and good for edge applications.

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