Design and Implementation of Real Time Face Recognition System (RTFRS)

Face recognition is a pattern recognition technique and one of the most important biometrics; it is used in a broad spectrum of applications. The accuracy is not a major problem that specifies the performance of automatic face recognition system alone, the time factor is also considered a major factor in real time environments. Recent architecture of the computer system can be employed to solve the time problem, this architecture represented by multi-core CPUs and many-core GPUs that provide the possibility to perform various tasks by parallel processing. However, harnessing the current advancements in computer architecture is not without difficulties. Motivated by such challenge, this paper proposes a Real Time Face Recognition System (RTFRS). In doing so, this paper provides the architectural design, detailed design, and four variant implementations of the RTFRS. Finally, this paper determines the speed up obtained for the three advanced implementations (i.e., Hybrid Parallel model, CPU Parallel model, and Hybrid Mono model) against the convention implementation (i.e., CPU Mono model). The practical results demonstrate that the Hybrid Parallel model gain highest speed up around 82X, CPU Parallel model also have a high speed up around 71X, and finally, the Hybrid Mono model gives a slight speed up about 1.04X