期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B3
页码：780-783
出版社：Copernicus Publications
摘要：Face recognition plays an important role in biometrics base personal identification. The need for reliable recognition and identification of interacting users is obvious. The biometrics recognition technique acts as an efficient method and wide applications in the area of information retrieval, automatic banking, control of access to security areas and so no. This paper describes a method of face recognition based on Principal Component Analysis (PCA) and wavelet decomposition. The proposed scheme exploits feature extraction capabilities of the Discrete Wavelet Transform Decomposition and invokes certain normalization techniques that increase its robustness to variations in facial geometry and illumination. Traditionally, to represent the human face, PCA is performed on the whole facial image. In this method, wavelet transform is used to decompose an image into different frequency subbands, and a mid-range frequency subband is used for PCA representation. In comparison with the traditional use of PCA, the proposed method gives better recognition accuracy and discriminatory power; further, the proposed method reduces the computational load significantly when the image database is large. Experimental results show that the proposed method is effective and possesses several desirable properties when it compared with many existing algorithms
