Aiming at the problems of missing real minutiae and increasing pseudo minutiae of lowquality fingerprint, and the typical fingerprint identification algorithm is too dependent on the accuracy of minutiae, a visually constrained enhanced triangulation fingerprint recognition algorithm is proposed. First, use triangle reconstruction to obtain the enhanced triangulation set according to the extracted minutiae points; then calculate the triangle feature vector, use the decrement verification for triangle matching to determine the matching minutiae pair, and use the visual constraint optimization; finally obtain the similarity according to the ratio of the matching point so as to complete the recognition. The international standard test libraries FVC2000DB2, FVC2006DB2 and FVC2006DB3 were used for comprehensive performance comparison experiments, and the EER rates of the algorithm were 432%, 264% and 798%, respectively. Compared with the Delaunay triangulation algorithm, the modified Delaunay triangulation algorithm can reduce the EER by 128%, 171% and 283%, compared with the extended triangulation algorithm by 126%, 052% and 258%, and compared with the SIFT algorithm by 089%, 297% and 003%, respectively. The experimental results show that the proposed algorithm does not need calibration and has good adaptability to the loss of real fine nodes and the increase of pseudo fine nodes caused by lowquality fingerprints.