Face recognition based on principal component analysis (PCA)

The most important thing in the pattern recognition process is image preprocessing. Image preprocessing is an important step in the pattern recognition process. Its purpose is to minimize the influence of external interference on the recognition target, and in accordance with the requirements of the face image recognition method standardize the image. In this paper, for the noise-free source image, based on the principal component analysis (PCA) feature extraction algorithm, the image is preprocessed, and the grayscale, normalization, geometric correction, filter transformation and so on are processed in the preprocessing stage.