Concerning the problem that two Dimensional (2D) palmprint images are eaasily to be forged and affected by noise, a three Dimensional (3D) palmprint recognition method based on Neighbor Ternary Pattern (NTP) and collaborative representation was proposed. Firstly, a shape index was used to map the surface geometric information of 3D palmprint into 2D data, avoiding the inaccurate description of 3D palmprint features by common mean value or Gaussian curvature mapping. Secondly, the shape index image was divided into several blocks, and NTP algorithm was used to extract texture features of divided shape index images. Finally, collaborative representation was used to classify the features. Experiments on 3D palmprint base show that compared with the classical algorithms, the proposed method has the best recognition effect with recognition rate of 99.52% and recognition time of 0.6738 s. The proposed method improves the recognition rate by 7.77%, 6.02%, 5.12% and 3.97% respectively compared to Local Binary Pattern (LBP), Local Ternary Pattern (LTP), CompCode and Mean Curvature Image (MCI) method; the proposed method reduces the recognition time by 6.7 s, 15.9 s and 61 s compared to Homotopy, Dual Augmented Lagrangian Algorithm (DALM) and SpaRSA method. The experimental results show that the proposed algorithm has good feature extraction and classification ability, which can effectively improve the recognition accuracy and reduce the recognition time.