전자공학회논문지 (Journal of the Institute of Electronics and Information Engineers)

  • 제52권10호
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  • Pages.129-136
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  • 2015
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  • 2287-5026(pISSN)
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  • 2288-159X(eISSN)
대한전자공학회 (The Institute of Electronics and Information Engineers)
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조명 변이에 강인한 하이브리드 얼굴 인식 방법

A Robust Hybrid Method for Face Recognition Under Illumination Variation

  • Choi, Sang-Il (Department of Computer Science and Engineering, Dankook University)
  • 투고 : 2015.07.14
  • 심사 : 2015.09.22
  • 발행 : 2015.10.25
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초록

본 논문에서는 조명 변이에 강인하게 동작 할 수 있는 하이브리드 얼굴 인식 방법을 제안한다. 이를 위해, 서로 다른 특성을 가진 조명 불변 특징 추출 방법으로부터 판별력 있는 특징들을 추출한다. 개별 방법들의 장점들을 효과적으로 활용하기 위해, 판별 거리 척도를 이용하여 각 특징들의 분별력을 측정하여 분별력이 높은 특징들로만 복합 특징을 구성하여 얼굴 인식에 사용한다. Multi-PIE, Yale B, AR, yale database들에 대한 실험 결과, 제안한 방법은 모든 database에 대해 개별 조명 불변 특징 방법들보다 우수한 인식 성능을 보여 주었다.

We propose a hybrid face recognition to deal with illumination variation. For this, we extract discriminant features by using the different illumination invariant feature extraction methods. In order to utilize both advantages of each method, we evaluate the discriminant power of each feature by using the discriminant distance and then construct a composite feature with only the features that contain a large amount of discriminative information. The experimental results for the Multi-PIE, Yale B, AR and yale databases show that the proposed method outperforms an individual illumination invariant feature extraction method for all the databases.

키워드

참고문헌

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