Journal of the Institute of Electronics Engineers of Korea CI (전자공학회논문지CI)

The Institute of Electronics and Information Engineers (대한전자공학회)
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A Study on Face Recognition Method based on Binary Pattern Image under Varying Lighting Condition

조명 변화 환경에서 이진패턴 영상을 이용한 얼굴인식 방법에 관한 연구

  • Kim, Dong-Ju (Division of IT Convergence, Daegu Gyeongbuk Institute of Science & Technology) ;
  • Sohn, Myoung-Kyu (Division of IT Convergence, Daegu Gyeongbuk Institute of Science & Technology) ;
  • Lee, Sang-Heon (Division of IT Convergence, Daegu Gyeongbuk Institute of Science & Technology)
  • 김동주 (대구경북과학기술원 IT융합연구부) ;
  • 손명규 (대구경북과학기술원 IT융합연구부) ;
  • 이상헌 (대구경북과학기술원 IT융합연구부)
  • Received : 2011.02.16
  • Accepted : 2012.03.05
  • Published : 2012.03.25
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Abstract

In this paper, we propose a illumination-robust face recognition system using MCS-LBP and 2D-PCA algorithm. A binary pattern transform which has been used in the field of the face recognition and facial expression, has a characteristic of robust to illumination. Thus, this paper propose MCS-LBP which is more robust to illumination than previous LBP, and face recognition system fusing 2D-PCA algorithm. The performance evaluation of proposed system was performed by using various binary pattern images and well-known face recognition features such as PCA, LDA, 2D-PCA and ULBP histogram of gabor images. In the process of performance evaluation, we used a YaleB face database, an extended YaleB face database, and a CMU-PIE face database that are constructed under varying lighting condition, and the proposed system which consists of MCS-LBP image and 2D-PCA feature show the best recognition accuracy.

본 논문에서는 MCS-LBP 이진패턴 영상과 2D-PCA 알고리즘을 이용한 조명 변화에 강인한 얼굴인식 시스템에 대하여 제안한다. 이진패턴 변환은 기존의 얼굴인식 및 표정인식 분야에 사용되는 기법으로, 일반적으로 조명 변화에 강인한 특성을 갖는다. 이에 본 논문에서는 기존의 LBP보다 조명 변화에 더 강인한 MCS-LBP를 제안하고, 더불어 2D-PCA 알고리즘과 결합하는 얼굴인식 시스템을 제안한다. 제안하는 얼굴인식 방법의 성능평가는 기존의 다양한 이진패턴 변환 영상과 얼굴인식에 널리 사용되고 있는 PCA, LDA, 2D-PCA 및 가버영상의 ULBP 히스토그램 특징을 사용하여 수행하였다. 다양한 조명변화 환경에서 구축된 YaleB, extended YaleB, CMU-PIE 등의 공인 얼굴 데이터베이스를 이용하여 실험한 결과, 제안하는 MCS-LBP영상과 2D-PCA 특징을 사용한 방법이 가장 우수한 인식 성능을 보였다.

Keywords

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