Robust encoding of local ordinal measures: A general framework of iris recognition

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Abstract

The randomness of iris pattern makes it one of the most reliable biometric traits. On the other hand, the complex iris image structure and various sources of intra-class variations result in the difficulty of iris representation. Although diverse iris recognition methods have been proposed, the fundamentals of iris recognition have not a unified answer. As a breakthrough of this problem, we found that several accurate iris recognition algorithms share a same idea - local ordinal encoding, which is the representation well-suited for iris recognition. After further analysis and summarization, a general framework of iris recognition is formulated in this paper. This work discovered the secret of iris recognition. With the guidance of this framework, a novel iris recognition method based on robust estimating the direction of image gradient vector is developed. Extensive experimental results demonstrate our idea. © Springer-Verlag Berlin Heidelberg 2004.

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Sun, Z., Tan, T., & Wang, Y. (2004). Robust encoding of local ordinal measures: A general framework of iris recognition. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3087, 270–282. https://doi.org/10.1007/978-3-540-25976-3_25

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