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首页> 外文期刊>Pattern Analysis and Applications >A new approach to the design of hybrid finer directional wavelet filter bank for iris feature extraction and classification using k-out-of-n:A post-classifier
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A new approach to the design of hybrid finer directional wavelet filter bank for iris feature extraction and classification using k-out-of-n:A post-classifier

机译：使用k-out-of-n的混合精细方向小波滤波器组设计虹膜特征的新方法：后分类器

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摘要

This paper presents a novel iris feature extraction scheme using two-dimensional non-separable, non-redundant, multi-scale hybrid finer directional wavelet filter bank and classification using fused post-classifier under non-ideal environmental conditions. The proposed approach overcomes limited directionality of wavelet transform. The designed filter bank converts the wavelet basis functions to a set of directional basis elements by employing the combination of designed bi-orthogonal wavelet filter bank and modified checkerboard-shaped filter bank (designed using triplet of half-band filters). The false rejection rate is reduced with the help of k-out-of-n:A rule. The proposed technique is capable to handle possible artifacts especially inaccurate iris localization, occlusion of eyelids, pupil, eyelashes, reflection on iris, non-linear deformation, head-tilt, etc. The performance of the proposed scheme is validated using CASIA-Iris V2.0, MMU1, and UBIRIS databases. Finally, the performance of proposed approach is compared with other existing iris recognition algorithms to demonstrate its potential.
机译：本文提出了一种新的虹膜特征提取方案，该方案使用二维不可分，非冗余，多尺度混合精细方向小波滤波器组，并在非理想环境条件下使用融合后分类器进行分类。所提出的方法克服了小波变换的有限方向性。设计的滤波器组通过结合设计的双正交小波滤波器组和改进的棋盘形滤波器组（使用三重半带滤波器设计），将小波基函数转换为一组方向性基元。借助k-out-of-n：A规则降低了错误拒绝率。所提出的技术能够处理可能的伪影，特别是虹膜定位不准确，眼睑闭塞，瞳孔，睫毛，虹膜反射，非线性变形，头部倾斜等。所提方案的性能已通过CASIA-Iris V2进行了验证。 .0，MMU1和UBIRIS数据库。最后，将所提方法的性能与其他现有虹膜识别算法进行比较，以证明其潜力。

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