基于Gabor小波编码的局部有序二值扩展改进虹膜识别

Jinyu Zuo, N. Schmid
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引用次数: 6

摘要

Daugman的虹膜识别算法于90年代初提出,经过不断的改进,仍然是虹膜领域最有效和可扩展的算法。该算法的编码部分依赖于Gabor小波的应用,Gabor小波在成像能力方面模仿人眼感受器场的能力。在这项工作中,我们设计并测试了一种算法,该算法既可以单独使用,也可以作为Gabor小波算法的自然扩展方案。它基于从原始未过滤图像中提取的局部有序信息。该方案具有以下优点:(1)它对虹膜图像中的一些非理想性具有鲁棒性;(2)由于局部有序信息的二值性,该方案可以完美地集成到传统的基于滤波器的识别系统中。所提出的方案被广泛地单独测试,并与基于Gabor小波的方法相结合。
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On a Local Ordinal Binary Extension to Gabor Wavelet-Based Encoding for Improved Iris Recognition
Daugman's iris recognition algorithm introduced in early 90s and later undergoing continuous refinements remains potentially the most efficient and scalable in iris field. The encoding part of the algorithm relies on application of Gabor wavelets that in terms of their imaging capabilities mimic capabilities of human eye receptor field. In this work, we design and test an algorithm that can be used both individually and as a natural extension scheme to Gabor wavelet-based algorithm. It is based on the local ordinal information extracted from original unfiltered images. This scheme holds a number of promises: (1) it is robust with respect to a number of nonidealities in iris images and (2) because of the binary nature of the local ordinal information this scheme can be flawlessly integrated into the traditional filter-based recognition systems. The proposed scheme was extensively tested individually and when combined with Gabor wavelet-based approach.
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