Several human being traits can be used as a robust and distinctive identifier for a given person. The palm region of the hand is one of these features that researchers in biometric fields have given a huge consideration in recent years. Many works have been proposed in the literature to design palmprint (an image acquired of the palm region) recognition framework. Extraction of prominent image local features is a critical module in most of these approaches. Local Binary Patterns (LBP) like methods, have emerged as one of the most effective feature extraction techniques. Despite a period of remarkable evolution, neither extensive and comprehensive evaluation nor comparison has been performed to date on a large number of LBP variants and non-LBP texture methods in palmprint recognition problem. Motivated by this, this paper aims to fill that gap and provide a comprehensive comparative study of the performance of a large number of recent texture descriptors in palmprint recognition. Extensive experimental results on the well-known constrained and unconstrained challenging palmprint databases, indicate that a number of tested local texture descriptors, which are evaluated for the first time on palmprint recognition, achieve promising results. Classification results are statistically compared through Wilcoxon signed rank test.

中文翻译：

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使用最新的局部纹理描述符进行掌纹识别：一项比较研究

可以将几种人的性状用作给定人的可靠且独特的标识符。手掌区域是生物识别领域的研究人员近年来高度重视的这些特征之一。在文献中已经提出了许多设计掌纹（掌区域的图像）识别框架的工作。在大多数这些方法中，提取突出的图像局部特征是至关重要的模块。类似局部二进制模式（LBP）的方法已经成为最有效的特征提取技术之一。尽管经历了一段显着的发展期，但迄今为止，尚未对掌纹识别问题中的大量LBP变体和非LBP纹理方法进行广泛而全面的评估或比较。受此启发，本文旨在填补这一空白，并对掌纹识别中大量最新纹理描述符的性能进行全面的比较研究。在著名的受约束和不受约束的挑战性掌纹数据库上的大量实验结果表明，在掌纹识别上首次进行评估的许多经过测试的局部纹理描述符均取得了可喜的结果。分类结果通过Wilcoxon符号秩检验进行统计比较。首次在掌纹识别方面进行了评估，取得了可喜的结果。分类结果通过Wilcoxon符号秩检验进行统计比较。首次在掌纹识别方面进行了评估，取得了可喜的结果。分类结果通过Wilcoxon符号秩检验进行统计比较。