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文章基本信息

  • 标题:Local Relation Map: A Novel Illumination Invariant Face Recognition Approach
  • 本地全文:下载
  • 作者:Lian Zhichao ; Er Meng Joo
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2012
  • 卷号:9
  • DOI:10.5772/51667
  • 语种:English
  • 出版社:SAGE Publications
  • 摘要:In this paper, a novel illumination invariant face recognition approach is proposed. Different from most existing methods, an additive term as noise is considered in the face model under varying illuminations in addition to a multiplicative illumination term. High frequency coefficients of Discrete Cosine Transform (DCT) are discarded to eliminate the effect caused by noise. Based on the local characteristics of the human face, a simple but effective illumination invariant feature local relation map is proposed. Experimental results on the Yale B, Extended Yale B and CMU PIE demonstrate the outperformance and lower computational burden of the proposed method compared to other existing methods. The results also demonstrate the validity of the proposed face model and the assumption on noise.
  • 关键词:Pattern recognition; Face recognition; Illumination variation
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