As a most important biometric solution for personal identification, iris recognition has received increasing attention in recent years. Based on the features of the stochastic iris textural information and local time-frequency properties of the wavelet transform, this paper proposes a new method for iris recognition using a wavelet-based multi-matching system, which includes a coarse matching and its refinement. For the low-frequency components of the wavelet multi-resolution decomposition, a statistical correlation approach is adopted for a coarse matching so that well-matched iris templates in a database can be picked out and need to be further identified. The wavelet modulus maxima are used to locate the sharp variation points, which are taken as iris feature points. A similarity measure based on the distances between the best-matched feature point pairs is taken for the refinement of the coarse matching. Our method well employs the iris morphological characteristics and the multi-matching process to improve the efficiency. The experimental results indicate the validity of the proposed method.


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    Title :

    Multi-Matching Process Based on Wavelet Transform for Iris Recognition


    Contributors:
    Ming, Xing (author) / Li, Zhihui (author) / Wang, Zhengxuan (author) / Zhu, Xiaodong (author)


    Publication date :

    2005-01-01


    Size :

    173580 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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