Recent years have witnessed a growing interesting in developing automatic palmprint recognition methods. Most of the previous works have concentrated on two dimensional (2D) palmprint recognition in the past decade. However, the shape information is lost in 2D plamprint images. What’s more, 2D plamprint recognition is not robust enough in practice since its data could be easily counterfeited or contaminated by noise. Consequently, three dimensional (3D) palmprint recognition is treated as an important alternative road to both enhance the performance and robustness of current available palmprint recognition systems. In this paper, we first explore geometrical information of 3D palmprint data by employing shape index formulation, from which Gabor wavelet features are then extracted. Furthermore, we first discover that by incorporating fragile bits information, the performance of coding strategy related 3D recognition method can be further improved. Experiments conducted on the public available 3D plamprint database validate that our method can obtain the highest recognition performance among the state-of-the-art methods estimated.