Digital information facial recognition based on PCA and its improved algorithm

Face recognition (PCA algorithm) based on principal component analysis method is a classic algorithm of digital information face recognition. This paper first analyzes the PCA algorithm and its basic principles. And in view of the shortage that it is affected by its subject facial expression changes and other factors, it designs the improved PCA algorithm, namely adding the image enhancement processing method, such as the local mean and standard deviation, to the original algorithm to increase the robustness of human face illumination and facial expression change during recognition. In addition, verify it on ORL face database and the results show that the improved PCA algorithm can get a higher resolution of the human face and up to 81.59% accuracy rate. The average growth of time-consuming is 0.378 seconds compared to traditional algorithms, and it is a fruitful improved algorithm.