Liao Fengxiang, Leng Lu, Yang Ziyuan, Zhang Bob
Jiangxi Province Key Laboratory of Image Processing and Pattern Recognition, Nanchang Hangkong University, 696 Fenghe Nan Avenue, Nanchang, 330063 Jiangxi, P. R. China.
College of Computer Science, Sichuan University, No. 24, South Section 1, First Ring Road, Chengdu 610065 Sichuan, P. R. China.
Int J Neural Syst. 2025 Aug;35(8):2550039. doi: 10.1142/S012906572550039X. Epub 2025 May 26.
Palmprint recognition is a pivotal biometric modality, renowned for its numerous advantages and applications in the field of biometrics. The Gabor filter is a classic and efficient texture feature extractor abstracted from the nervous system. The existing palmprint texture coding methods only focus on first-order texture features (1TFs), while neglecting discriminative second-order texture features (2TFs). Therefore, this paper proposes multi-order extensions for state-of-the-art (SOTA) palmprint texture coding methods, which makes full usage of 1TFs and 2TFs. A filter is used to extract 1TFs from the palmprint image, and the same filter is applied to extract 2TFs from 1TFs. Here, different methods employ various filters to extract diverse textures. Due to the simultaneous participations of 1TFs and 2TFs in multi-order extension codes, more discriminative features are extracted and fused. The experimental results on three public databases, including contact, noncontact and multispectral acquisition types, show that the accuracies of all the palmprint texture coding methods are remarkably improved by multi-order extension, establishing it as a general framework extendable to other texture-based recognition tasks.
掌纹识别是一种关键的生物特征识别方式，因其在生物特征识别领域的众多优势和应用而闻名。伽柏滤波器是一种从神经系统中抽象出来的经典且高效的纹理特征提取器。现有的掌纹纹理编码方法仅关注一阶纹理特征（1TFs），而忽略了具有区分性的二阶纹理特征（2TFs）。因此，本文提出了对当前先进（SOTA）掌纹纹理编码方法的多阶扩展，该扩展充分利用了1TFs和2TFs。使用一个滤波器从掌纹图像中提取1TFs，并将相同的滤波器应用于从1TFs中提取2TFs。在此，不同的方法采用各种滤波器来提取不同的纹理。由于1TFs和2TFs同时参与多阶扩展编码，提取并融合了更多具有区分性的特征。在包括接触式、非接触式和多光谱采集类型的三个公共数据库上的实验结果表明，通过多阶扩展，所有掌纹纹理编码方法的准确率都得到了显著提高，使其成为一个可扩展到其他基于纹理的识别任务的通用框架。
