3D Face Recognition System with Compression
Wei Jen Chew, Kah Phooi Seng, Wai Chong Chia, Li-Minn Ang, Li Wern Chew · 2009
Abstract — Usage of 3D images for face recognition has become more popular in the past few years since they are not affected by pose changes. Hence, there exists a need to store or transmit 3D images efficiently. This is important when increasing amount of 3D images is needed to be stored in a limited space or sent over a fixed bandwidth channel. A possible solution is to compress the 3D image. Unfortunately, this may cause the recognition rate to drop. In this paper, a 3D face range recognition system with compression is proposed and the effect of using compressed 3D range images on the recognition rate is investigated. The Set Partitioning in Hierarchical Trees (SPIHT) coding technique is proposed to be used for the compression. This technique is an improvement of the Embedded Zerotree Wavelet (EZW) coding technique. From the simulation results, when comparing uncompressed probe images and probe images compressed using SPIHT coding, the compressed image recognition rate ranges from being lower to being slightly higher than uncompressed probe image recognition rate, depending on bit rate. This proves that a 3D face range recognition system using compressed images is a feasible alternative to a system without using compressed images and should be investigated since the benefits like smaller file storage size, faster image transmission time and better recognition rates are important. Index Terms—3D face recognition, 3D range image compression, SPIHT. I.