linear discriminant analysis for face detection to overcome segregate investigation
T.A.Akchaiah,E.Deepika,A.Naresh Kumar
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:4 Issue:3 Year: 29 March,2016 Pages:512-518
Abstract
Face (facial) recognition is the identification of humans by the unique characteristics of their Faces. Face recognition technology is the least intrusive and fastest bio-metric technology. It works with the most obvious individual identifier the human face. With increasing security needs and with advancement in technology extracting information has become much simpler. We aims on building an application based on face recognition using different algorithms and comparing the results. The basic purpose being to identify the face and retrieving information stored in computer. It involves two main steps. First to identify the distinguishing factors in image n storing them and Second step to compare it with the existing images and returning the data related to that image. The various algorithms used for face detection are PCA Algorithm. Face recognition is an important application of Image processing owing to its use in many fields. The project presented here was developed after study of various faces recognition methods and their efficiencies. An effective and real time face recognition system based on video and is developed by asp.net. The recognition produced using 3 different matching techniques are compared and the results have been presented. The correct recognition rate achieved using the normal PCA is 92.3% in comparison to the 73.1% for the LDA with Euclidean distance.
Kewords
Face recognition, linear discriminant analysis, discrimination analysis, kernel principal component analysis.
Reference
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