• Title/Summary/Keyword: kernel D-DLA

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Face Recognition Evaluation of an Illumination Property of Subspace Based Feature Extractor (부분공간 기반 특징 추출기의 조명 변인에 대한 얼굴인식 성능 분석)

  • Kim, Kwang-Soo;Boo, Deok-Hee;Ahn, Jung-Ho;Kwak, Soo-Yeong;Byun, Hye-Ran
    • Journal of KIISE:Software and Applications
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    • v.34 no.7
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    • pp.681-687
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    • 2007
  • Face recognition technique is very popular for a personal information security and user identification in recent years. However, the face recognition system is very hard to be implemented due to the difficulty where change in illumination, pose and facial expression. In this paper, we consider that an illumination change causing the variety of face appearance, virtual image data is generated and added to the D-LDA which was selected as the most suitable feature extractor. A less sensitive recognition system in illumination is represented in this paper. This way that consider nature of several illumination directions generate the virtual training image data that considered an illumination effect of the directions and the change of illumination density. As result of experiences, D-LDA has a less sensitive property in an illumination through ORL, Yale University and Pohang University face database.