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http://dx.doi.org/10.12673/jkoni.2012.16.1.151

Age of Face Classification based on Gabor Feature and Fuzzy Support Vector Machines  

Lee, Hyun-Jik (Division of Computer Engineering, Mokwon University)
Kim, Yoon-Ho (Division of Computer Engineering, Mokwon University)
Lee, Joo-Shin (Division of Electronic & Information, Cheongju University)
Publication Information
Journal of Advanced Navigation Technology / v.16, no.1, 2012 , pp. 151-157 More about this Journal
Abstract
Recently, owing to the technology advances in computer science and image processing, age of face classification have become prevalent topics. It is difficult to estimate age of facial shape with statistical figures because facial shape of the person should change due to not only biological gene but also personal habits. In this paper, we proposed a robust age of face classification method by using Gabor feature and fuzzy support vector machine(SVM). Gabor wavelet function is used for extracting facial feature vector and in order to solve the intrinsic age ambiguity problem, a fuzzy support vector machine(FSVM) is introduced. By utilizing the FSVM age membership functions is defined. Some experiments have conducted to testify the proposed approach and experimental results showed that the proposed method can achieve better age of face classification precision.
Keywords
age of face; classification; feature vector; Gabor feature; FSVM;
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