The design of face recognition system based on ARM9 embedded platform

A specific face recognition system designed on ARM9 architecture embedded platform is proposed in this paper. By using the method of skin model combined with Haar-like features to detect faces and PCA (principal component analysis) dimension declining algorithm to recognize the face. Firstly, the libraries of QT and OpenCV are transplanted into the ARM9 platform which constructs the basis of all the programs in the system. In addition, the training sample data are made and then transmitted to the embedded system. After that the processed face images are recognized by using the nearest distance algorithm. Experiments show that this design on the platform of ARM 9 embedded system has boosted the efficiency of embedded face recognition system, especially in the case of needing huge data processing.