Journal of Advanced Navigation Technology (한국항행학회논문지)

The Korean Navigation Institute (한국항행학회)
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Age of Face Classification based on Gabor Feature and Fuzzy Support Vector Machines

Gabor 특징과 FSVM 기반의 연령별 얼굴 분류

  • 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)
  • 이현직 (목원대학교 컴퓨터공학부) ;
  • 김윤호 (목원대학교 컴퓨터공학부) ;
  • 이주신 (청주대학교 전자정보공학부)
  • Received : 2012.02.01
  • Accepted : 2012.02.28
  • Published : 2012.02.29
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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.

최근 영상처리기술과 컴퓨터과학의 발달로 연령변화에 따른 얼굴형상 분류 방법은 일반적인 주제가 되었다. 사람의 연령별 얼굴분류는 생물학적 유전자와 오랜 생활의 식습관으로 인하여 얼굴 형상이 변하기 때문에 통계적 형상만으로 예측하기란 쉽지 않다. 본 논문에서는 Gobor 특징과 fuzzy SVM 기법을 이용하여 연령대별 얼굴분류 기법을 제안하였다. Gabor 웨이블릿 함수는 얼굴의 특징벡터를 구하기 위하여 사용되고 연령대별 얼굴형상 구분이 애매모호한 문제를 해결하기 위해 fuzzy SVM 기법을 이용하여 연령별 소속 함수를 정의하였다. 제안한 방법으로 연령별 소속함수에 따른 얼굴 분류 실험을 수행하였고 제안한 방법의 타당성을 확인하였다.

Keywords

References

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