FPGA Based Facial Recognition System

Introduction: Face recognition research is motivated not just by fundamental security concerns, but also by the fact that it is required in many practical applications where human identity is required. Rapid improvements in technology such as digital cameras, the internet, mobile devices, and technological demands on security have facilitated and encouraged face recognition as one of the key biometric technologies. Face detection, feature extraction, and classification methods for face identification utilizing hardware description language HDL implemented in a Field Programmable Gate Array are investigated in this paper (FPGA).The research goals include.

Methods: The Viola-Jones algorithm for face detection was developed, followed by developing an algorithm for feature extraction using Artificial Neural Networks (ANN),and finally feature matching using Hamming Distance. The whole system was implemented on FPGA, using VHDL.

Results: The system successfully identifies the eye region of the face from the image, and extracts the features of each image then perform matching. The program output or display a result of image matched or image not matched. The execution time of the overall system speeds up due to the parallel processing of FPGA.

Conclusion: The program was able to distinguish between two images of people based on their eye image, as well as detect minor expressional changes in the test image. Designing the full algorithm using FPGA help in speeding up the execution time of the processes, which gives the opportunity to build the system to work in real time with low cost due to its flexibility.