We propose a novel approach to 3D hand geometry-based person authentication using projected light patterns. Instead of explicitly c omputing a depth map of the palm for recognition, we capture the depth information in the deformations of a projected texture pattern, and use it directly for recognition. The deformed pattern is c haracterized using local texture measures, which can encode the certain depth characteristics of the palm. An authentication system built using the proposed technique achieves an equal error rate of 0.84% on a dataset of 1341 samples collected from 149 users, as opposed to 4.03% using traditional 2D features on an identical dataset. The approach is robust as well as computationally efficient and could be applied to other 3D object recognition problems as well. © 2008 IEEE.