Abstract: In highconcurrency, multiinstance and other business simulation scenarios,this paper tested the process of face detection, feature extraction, feature matching retrieval, and optimized the efficiency and accuracy of face recognition algorithm. The paper used MTCNN, improved Insightface algorithm and Faiss frame, based on LFW data set, compared the extracted features with the API provided by Face++. The analysis results show that the precision of feature extraction is 99.76% for 1v1 and 95.23% for 1v N. The efficiency of feature extraction is 7.84 per second. The efficiency of feature matching is two orders of magnitude higher than that of traditional algorithms. The research on this face recognition technology provides technical support for railway to carry out the dynamic security control of super scale person image database in the future.