A novel Face Recognition Method based on Feature Fusion of Global and Local Structure

Abstract

Principal component analysis (PCA) and linear discriminant analysis (LDA) are an extraction method based on the global structure features. Locality preserving projection (LPP) and orthogonal laplacianfaces (OLF) methods are based on the local structure features. The local structure features cannot be characterized in the global structure features, and the global structure features are ignored in the local structure. For this, it is proposed in this paper a novel method named fusion of global and local structure (GLSF) to fusion the feature extracted from PCA and LDA into LPP, considering both the global and the local structure. Experiments on ORL and Yale show higher recognition accuracy than PCA, LDA, LPP, OLF, and so on.