期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2011
卷号：1
期号：1-1
出版社：Seventh Sense Research Group
摘要：—wouldn’t you love to replace password based access control to avoid having to reset forgotten password and worry about the integrity of your system? Wouldn’t you like to rest secure in comfort that your healthcare system does not merely on your social security number as proof of your identity for granting access to your medical records? Because each of these questions is becoming more and more important, access to a reliable personal identification is becoming increasingly essential .Conventional method of identification based on possession of ID cards or exclusive knowledge like a social security number or a password are not all together reliable. ID cards can be lost, forgotten or misplaced. But a face is undeniably connected to its owner. It cannot be borrowed stolen or easily forged. Face recognition has always been a fascinating research area. Face recognition is the preferred mode of identification by humans it is natural, robust and nonintrusive. Face recognition being the most effective and natural technique to identify a person since it is the same as the way human does and there is no need to use special equipments. A lot of algorithms have been proposed for solving face recognition problem. Principal component analysis (PCA) is a classical and successful method for face recognition. Self organizing map (SOM) has also been used for face space representation. This paper makes an attempt to enhance these two techniques and describe the use of PCA and SOM in facial recognition. It also explains the performance result when the two algorithms are combined together. The advantage in combining the two techniques is that the reduction in data is higher but at the cost of recognition rate.
关键词：Face Recognition; SOM (Self Organizing Map); PCA (Principal Component Analysis); LDA (Linear Discriminant Analysis); ORL (Olivetti Research Laboratory)
