Numerous perceptual hashing algorithms have been developed for identification and verification of multimedia objects in recent years. Many application schemes have been adopted for various commercial objects. Developers and users are looking for a benchmark tool to compare and evaluate their current algorithms or technologies. In this paper, a novel benchmark platform is presented. PHABS provides an open framework and lets its users define their own test strategy, perform tests, collect and analyze test data. With PHABS, various performance parameters of algorithms can be tested, and different algorithms or algorithms with different parameters can be evaluated and compared easily.
Fisherfaces algorithm is a popular method for face recognition.However,there exist some unstable com- ponents that degrade recognition performance.In this paper,we propose a method based on detecting reliable com- ponents to overcome the problem and introduce it to 3D face recognition.The reliable components are detected within the binary feature vector,which is generated from the Fisherfaces feature vector based on statistical properties,and is used for 3D face recognition as the final feature vector.Experimental results show that the reliable components fea- ture vector is much more effective than the Fisherfaces feature vector for face recognition.
