ing at the problems of non-contact images acquisition such as blur phenomenon, poor system identification systems and poor recognition effect, a palmprint and palm vein feature fusion recognition method based on block strengthened local directional pattern(BSLDP) and canonical correlation analysis is proposed. Firstly, we improve the traditional local directional pattern(LDP),and proposed the BSLDP algorithm to obtain the texture direction feature of palmprint and palm vein images. Secondly, the palmprint and palm vein feature fusion is realized effectively based on the canonical correlation analysis. Finally, the match identification is realized based on the chi-square distance. The experimental results show that the equal error rate is only 0.63% and 1.21% in the CASIA-M and the self-built non-contact image database. The results indicate that compared with other traditional and newest algorithms, the proposed method can eliminate redundant information, retain accurate feature information of palmprint and palm vein and improve system identification performance.