Face Recognition Technology Research And Application Based On Subspace

Computer face recognition technology is an important biological feature extraction techniques, In this paper, the techniques focus on a static facial image recognition method by feature extraction and feature classification study.This paper study the feature extraction part of the in-depth based on principal component analysis (PCA) for face recognition principle and the implementation process, thus the introduction of Fisher linear discriminant method can solve the problem of face recognition under illumination effects. In order to solve the linear discriminant in the small sample size problem, this paper presents a solution to PCA + LDA.In the data pre-processing, the study based on skin color and eye characteristics of the location of human face positioning method, according to the location of the human eye out of accurate positioning of the upper and lower face left and right borders to carry out the exact location of face.In the applications, Face identifacation based on color features and the human eye's method of precise positioning of face detection and positioning, selection of principal component analysis to extract features side, using embedded locks and Portrait attendance system as a basis analysis for experiment .The results proved to be Portrait achieved through the recognition effect.