The biometric feature, iris, has advantages in person identification, such as complex texture, almost unchanged throughout the lifespan. Compared with the famous methods propose by Daugman and Boles, the system of Yong Zhu, et al., not only takes good use of the 2D texture, but also is more robust for using statistic values of the wavelet transformed images as features for recognition. Because wavelet transform is time consuming, a volume holography opto-electronic hybrid system with high parallelism is constructed in this paper. Li Ding, et al., introduced wavelet packet transform into an optical recognition system based on volume holography to reduce the number of images stored in the photo-refractive crystal. By joint best basis selection, eigen-images corresponding to the best wavelet packet bases are generated and stored to replace the reference images. This replacement results in high compression. Theoretical analysis and experimental results both show their scheme achieves significant compression and accurate recognition at the same time. Wavelet packet compression is also utilized in our system. But the best basis selection algorithm is modified. For iris identification, we use the recognition capacity of each wavelet packet basis instead of the entropy because the latter is not for recognition. Furthermore, in the post-processing stage, we use statistic features, like Yong Zhu, to represent each iris pattern which makes the system more robust to the errors caused by optical system. So our system combines the advantages of optics parallelism, high image compression and accuracy of digital processing. Simulation results show a high identification rate is obtained.