An Exploratory Survey on Various Face Recognition Methods Using Component Analysis

Abstract: Development in Human Computer Interactions (HCI) helps in budding user friendly systems to communicate with computers. One of the fundamental techniques that aid Human Computer Interaction (HCI) is face recognition. Face recognition is one of the most successful applications of image analysis and pattern recognition. Principle Component Analysis (PCA) is considered as the first real time face recognition technology. This paper compares the different PCA methods with standard PCA using eigenfaces. The methods considered in this paper are Kernel PCA, PCA with Image Gradient Orientation, PCA with Singular Value Decomposition and Diagonal PCA with KNN. This paper also suggests a statistical method for face recognition using the component analysis of difference image.

Keywords: Image Processing; Face Recognition PCA; IGO PCA; KPCA; PCA with SVD; DiaPCA