期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2014
卷号：5
期号：1
页码：84-87
出版社：TechScience Publications
摘要：Nowadays, Face Recognition is one of the most popular topics in Image Processing and Computer Vision. This heightened popularity is because of its non-intrusiveness, userfriendliness and immense application in fraud detection, law enforcement, surveillance and other security purposes. In this paper, we present four approaches for Facial Detection. The first approach we have exhibited is Normalized Cross Correlation which also has applications in pattern recognition, cryptanalysis, single particle analysis, and neurophysiology. For reliability, the output of correlation should be sharply peaked. The second approach, Peak to Side lobe Ratio (PSR) is used to measure the peak sharpness. The third approach uses one of the most important features of face i.e. eyes. The distance between the eyes being variable helps in classifying a person. The fourth approach Principal Component Analysis (PCA) is one of the traditional methods implemented for Face Recognition. Experimental results on GTAV database and Yale database shows that these approaches show sufficiently good results and is robust to illumination variation.
