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Evaluation of Ripplet Transform as a Texture Characterization for Iris Recognition

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Abstract

Being a unique characterization of individuals, iris plays an important role for biometric identification utilized for individual authentication. A unique method based on Ripplet transform is explored for iris recognition application. Four features derived from Ripplet transform coefficients, namely average energy (AE),first absolute moment (FAM), variance (V) and entropy (E), are experimentally tested using statistical independent t test analysis, and it has been proved that entropy is an efficient and prominent feature which characterizes iris texture uniquely. The proposed method gives a maximum accuracy rate of 98.33% on CASIA V1.0 database.

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Authors and Affiliations

  1. CS2S Technology Pvt. Ltd., Pune, 411041, Malvika Arcade, Narhe, India

    suchitra Khoje

  2. Department of Electronics & Telecommunication Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, 411018, India

    Sagar Shinde

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  1. suchitra Khoje
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  2. Sagar Shinde
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Khoje, s., Shinde, S. Evaluation of Ripplet Transform as a Texture Characterization for Iris Recognition. J. Inst. Eng. India Ser. B 104, 369–380 (2023). https://doi.org/10.1007/s40031-023-00863-6

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  • DOI: https://doi.org/10.1007/s40031-023-00863-6

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