Design and implementation of an embedded face recognition system on DM642

Abstract

In this paper an embedded system based on TMS320DM642 DSP to implement face recognition in real environment is designed. An AdaBoost based face detection algorithm using Haar features is designed to detect the face. After an active face is detected, cubic interpolation is employed to scale the facial image to the predefined size, and histogram equalization will also be performed to enhance the contrast of the facial image. An embedded hidden Markov model with seven super states and total 36 embedded states is constructed to recognize the detected face. The hardware framework and software design are also illustrated in this paper, and experiments based on simulator and designed hardware platform are performed. The results show that the proposed system can achieve 83% recognition rate under normal lighting condition and meets the requirements of real environment applications. © 2012 Springer-Verlag Berlin Heidelberg.