Iris Liveness Detection using Fusion of Thepade SBTC and Triangle Thresholding Features with Machine Learning Algorithms

Sudeep D. Thepade, Lomesh R. Wagh
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Abstract

Conventional security systems are often plagued by inherent flaws, leading to frequent security breaches. To address these vulnerabilities, automated biometric systems have emerged, leveraging individuals' physiological and behavioural traits for precise identification. Among these biometric modalities, iris-based authentication is a highly reliable, distinctive, and contactless method for user recognition. This research endeavours to enhance the accuracy of iris liveness detection by combining features extracted from the TSBTC n-Ary (Thepade’s Sorted Block Truncation Coding) method with those derived from the Triangle Thresholding method. Two distinct datasets, namely IIIT Delhi and Clarkson 2015, have been employed to evaluate the efficacy of these combined features. The study involves extracting features from three sources: TSBTC, TSBTC+Triangle, and Triangle methods. These features are subsequently input into the WEKA tool, which employs various classifiers to assess accuracy. The findings of this investigation reveal a notable increase in the accuracy of Iris Liveness Detection (ILD) by incorporating handcrafted techniques like TSBTC in conjunction with the Thresholding method. In essence, this research underscores the potential for improving the robustness of security systems by harnessing the synergy of distinct biometric methods, thereby mitigating the shortcomings of conventional security systems and fortifying the foundations of secure user authentication.
利用机器学习算法融合 Thepade SBTC 和三角阈值特征进行虹膜有效性检测
传统的安全系统往往存在固有缺陷,导致安全漏洞频发。为了解决这些漏洞,自动生物识别系统应运而生,利用个人的生理和行为特征进行精确识别。在这些生物识别模式中,基于虹膜的身份验证是一种高度可靠、独特和非接触式的用户识别方法。本研究通过将从 TSBTC n-Ary(Thepade 排序块截断编码)方法中提取的特征与从三角阈值法中提取的特征相结合,努力提高虹膜有效性检测的准确性。我们采用了两个不同的数据集,即 IIIT Delhi 和 Clarkson 2015,来评估这些组合特征的功效。研究涉及从三个来源提取特征:TSBTC、TSBTC+三角形和三角形方法。这些特征随后被输入 WEKA 工具,该工具采用各种分类器来评估准确性。研究结果表明,通过将 TSBTC 等手工技术与阈值法结合使用,虹膜有效性检测(ILD)的准确性显著提高。从本质上讲,这项研究强调了通过利用不同生物识别方法的协同作用来提高安全系统稳健性的潜力,从而减轻传统安全系统的缺点,巩固安全用户身份验证的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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