For the issues that the existing solutions for palmprint identification can't be very good to extract multi-resolution characteristic, this paper proposed a palmprint recognition scheme based on dual-tree complex wavelet transform (DT-CWT) and Levenberg-Marquardt (LM) neural network. Firstly, it convertsthe color image into gray image. Then, the region of interest (ROI) is extracted from the palm image, and constructed a histogram. Then, this scheme uses DT-CWT for 6 layers of wavelet decomposition and obtains the characteristic coefficients, and calculatesthe maximum value, average value and median value of the characteristic coefficients respectively. Finally, it uses LM neural network to make recognition and classification of palmprint. Experimental results on CASIA database show that the recognition rate of the proposed scheme has high recognition rate and lower recognition time.