The work aims to study the application of point feature extraction algorithm in lithium battery screen printing image registration, in order to improve the accuracy of lithium battery screen printing image registration and solve the problems of missing detection and false alarm in the quality inspection. The lithium battery screen printing image registration based on point feature was summarized. Firstly, the development of point feature extraction algorithm was concluded. Then, five classical point feature extraction algorithms including Harris, SIFT, SURF, ORB and AKAZE were analyzed and their improved algorithms in recent years were introduced. Finally, the battery screen images were tested for registration and experiment effect was analyzed by several evaluation technologies to summarize the advantages, disadvantages and applicability of different point feature extraction algorithms in lithium battery screen printing image registration. The point feature extracted by AKAZE had higher repetition rate and matching accuracy rate and the positioning error after registration was controlled within one pixel, but the scale invariance of AKAZE algorithm was poor. Compared with the other 4 algorithms, AKAZE algorithm has high reliability and stability, which can meet the real-time and efficient requirements of lithium battery screen printing image registration.