文章基本信息

标题：An Effective Approach for Face Recognition using PCA and LDA on Visible and IR images
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作者：Rupish Arora ; Amit Doegar
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2016
卷号：32
期号：1
页码：44-48
DOI：10.14445/22312803/IJCTT-V32P108
出版社：Seventh Sense Research Group
摘要：Now days, security is required everywhere and is one of the main concern. It is required in network security, telecommunication, security of data, in airport, in homes or the security of human beings. In computer science, biometrics is used for identification and to control access. It is also used to identify individuals in groups. Among various biometrics, the face of a human being plays an important role for identification. From last so many years, face recognition has become a challenging and interesting research. A large number of face recognition algorithms have been developed which include PCA, LDA, ICA and so on. Each technique has its own advantage and drawback. In this paper, a combination of PCA and LDA is implemented for face recognition on Normal and IR images, which results in more accurate output of the matched test input. The ORL database has been used for visible facial images, and CASIA dataset has used for IR facial images.
关键词：Eigenvector; Infrared Images; LinearDiscriminant Analysis; Principal Component Analysis; Visual Image.