Face Recognition System Based on Kernel Principle Component Analysis and Fuzzy-Support Vector Machine
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Abstract
In recent year, Face recognition system has taken much attention and used for different types of purposes for instance web application authentication, online investment and banking, mobile authentication, smart home security, virtual reality, database management and retrival etc.. In this paper, we are going to proposed a Face Recognition System by using Kernel Principal Component Analysis method and Fuzzy Support Vector Machines. Kernel Principal Component Analysis is used to play the main role in features extractor and Fuzzy Support Vector Machines are used to treat the face classification problem. Many studies were done on the Cambridge ORL Face database to assess the achievements and performance of the Face Recognition System. As well as comparisons between Kernel Principal Component Analysis and other component abstraction methods such as Principle Component Analysis and Linear discriminated Analysis and also compressions between Fuzzy Support Vector Machines and other classification methods such as Artificial Neural Networks are done. The experimental results show that the proposed methods give better results than other methods.
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