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An Efficient Iris Recognition System Based on Intersecting Cortical Model Neural Network

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  • Guangzhu Xu

    (Lanzhou University, China)

  • Zaifeng Zang

    (Three Gorges University, China)

Abstract

Iris recognition has been shown to be very accurate for human identification. In this article, an efficient iris recognition system based on Intersecting Cortical Model (ICM) neural network is presented which includes two parts mainly. The first part is image preprocessing which has three steps. First, iris location is implemented based on local areas. Then the localized iris area is normalized into rectangular region with a fixed size. At last the iris image enhancement is implemented. In the second part, the ICM neural network is used to generate iris codes and the Hamming Distance between two iris codes is calculated to measure the dissimilarity of them. In order to evaluate the performance of the proposed algorithm, CASIA v1.0 iris image database is used and the recognition results are encouraging.

Suggested Citation

  • Guangzhu Xu & Zaifeng Zang, 2008. "An Efficient Iris Recognition System Based on Intersecting Cortical Model Neural Network," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 2(3), pages 43-56, July.
    • Handle: RePEc:igg:jcini0:v:2:y:2008:i:3:p:43-56
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