As an emerging biometric technology, palmprint recognition technology has been researched widely and developed rapidly, which is well known for its high verification accuracy, low-price capture device, high reliability and user acceptance. Feature extraction as a core part of palmprint recognition, can effectively extract the characteristics or not, largely determines the system recognition rate. Reviewing current feature extraction research, we roughly group the palmprint feature extraction algorithms into four categories: structure-based, statistics-based, subspace-based and texture & transform domain feature based methods. The purpose of this paper is to provide an updated survey of palmprint feature extraction. After analyzing the state-of-the-art methods, the performance of various methods was compared and the future tendency was also discussed.