Fast Neural Implementation of PCA for Face Detection

Principle Component Analysis (PCA) has many different important applications especially in pattern detection such as face detection / recognition. Therefore, for real time applications, the response time is required to be as very small as possible. In this paper, new implementation of PCA for fast face detection is presented. Such new implementation is designed based on cross correlation in the frequency domain between the input image and eigenvalues (weights). Simulation results show that the proposed implementation of PCA is faster than conventional one.