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An efficient iris localization algorithm based on standard deviations

机译:一种基于标准差的有效虹膜定位算法

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摘要

There has been a rapid increase in the need of accurate and reliable personal identification technologies in recent years. Among all the biometric techniques known, iris recognition is taken as one of the most promising methods, due to its low error rates without being invasive. Usually an iris recognition system consists of four steps: image acquisition, preprocessing, feature extraction and identification or verification. Among these steps, iris localization is a necessary and important step in iris preprocessing. In order to be more feasible in real world application environment, the performance is a key factor. In this paper, we propose an efficient localization algorithm using standard deviation which is optimized for performance. Overall it achieves a promising result on various iris datasets compared to previous work. Besides, our method gets 52% execution time deduction compared to a traditional implementation reference for the localization.
机译:近年来,对准确和可靠的个人识别技术的需求迅速增长。在所有已知的生物识别技术中,虹膜识别被认为是最有前途的方法之一,这是因为虹膜识别的误码率低而没有侵入性。通常,虹膜识别系统包括四个步骤:图像获取,预处理,特征提取以及识别或验证。在这些步骤中,虹膜定位是虹膜预处理中必不可少的重要步骤。为了在现实世界的应用环境中更加可行,性能是关键因素。在本文中,我们提出了一种使用标准偏差的高效定位算法,该算法针对性能进行了优化。总体而言,与以前的工作相比,它在各种虹膜数据集上均取得了可喜的结果。此外,与传统的本地化实现参考相比,我们的方法减少了52%的执行时间。

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