Real-Time Facial Recognition System—Design, Implementation and Validation
M.V. Sethu Meenakshi · Journal of signal processing theory and applications · 2012
This paper presents the design, implementation and validation of a Digital Signal Processor (DSP)-based Prototype facial recognition and verification system. This system is organized to capture an image sequence, find facial features in the images, and recognize and verify a person. The current implementation uses images captured using a WebCam, compares it to a stored database using methods of Principal Component Analysis (PCA) and Discrete Cosine Transform (DCT). In the beginning, real-time validation of the identification of the captured images is done using a PC-based system with algorithms developed in MATLAB. Next, a TMS320C6713DSP-based prototype system is developed and validated in real-time. Several tests were made on different sets of images, and the performance and speed of the proposed system measured in real environment. Finally, the result confirmed that the proposed system can be applied to various applications which are impossible in conventional PC-based systems. Also, better results were observed from DCT analysis than PCA results.