Multi-Order Extension Codes for Palmprint Recognition

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.