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Extracting and analyzing iris textures for biometric recognition has beenextensively studied. As the transition of iris recognition from lab technologyto nation-scale applications, most systems are facing high complexity in eithertime or space, leading to unfitness for embedded devices. In this paper, theproposed design includes a minimal set of computer vision modules andmulti-mode QC-LDPC decoder which can alleviate variability and noise caused byiris acquisition and follow-up process. Several classes of QC-LDPC code fromIEEE 802.16 are tested for the validity of accuracy improvement. Some of thecodes mentioned above are used for further QC-LDPC decoder quantization,validation and comparison to each other. We show that we can apply DynamicPartial Reconfiguration technology to implement the multi-mode QC-LDPC decoderfor the iris recognition system. The results show that the implementation ispower-efficient and good for edge applications.

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