OSPP Face Recognition Using Meta-Heuristic Algorithm
IOSR Journal of Computer Engineering
Face recognition has drawn dramatic attention due to the advancement of pattern recognition technologies. Face recognition systems have reached a level of maturity under certain conditions but still the performance of face recognition algorithms are easily affected by external and internal variations. Thus many well-known algorithms have been proposed to overcome these challenging problems. Here we are trying to use one sample face image of individual for training the whole system which will
... ystem which will not only reduce labouring effort for the collection and also reduce cost for storing and processing them. One sample per person face recognition (OSPP) is considered as a challenging problem in face recognition community and lack of samples leads to performance deterioration. Here face recognition is performed by application of the swarm optimization algorithms  . It was found out that the underlying foraging principle and the swarm optimization can be integrated into evolutionary computational algorithms to provide a better search strategy for finding optimal feature vectors for face recognition. Finally, it is believed that the particle swarm optimization may be useful for the development of face recognition system. A meta-heuristic algorithm PSO is used that makes few or no assumptions about the problem being optimized and can search very large spaces of candidate solutions and also used for classifying purpose.