Palmprint recognition technology is an emerging and effective biometric technology, with palmprint images containing various unique features that can be utilized for individual identity verification, including principal lines, wrinkles, ridges, and so forth. Various palmprint recognition methods based on different feature types have been developed, encompassing line-based approaches, orientation-based methods, texture-based techniques, subspace learning-based strategies, and deep learning-based approaches. This paper reviews and introduces the orientation-based methods, with a particular focus on the feature extraction and feature matching stages in palmprint recognition, which are of paramount importance.