Separability Oriented Preprocessing for Illumination-Insensitive Face Recognition

  • Hu Han
  • Shiguang Shan
  • Xilin Chen
  • Shihong Lao
  • Wen Gao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7578)


In the last decade, some illumination preprocessing approaches were proposed to eliminate the lighting variation in face images for lighting-invariant face recognition. However, we find surprisingly that existing preprocessing methods were seldom modeled to directly enhance the separability of different faces, which should have been the essential goal. To address the issue, we propose to explicitly exploit maximizing separability of different subjects’ faces as the preprocessing objective. With this in mind, a novel approach, named by us Separability Oriented Preprocessing (SOP), is proposed to enhance face images by maximizing the Fisher separability criterion in scale-space. Extensive experiments on both laboratory-controlled and real-world face databases using different recognition methods show the effectiveness of the proposed approach.


Separability oriented illumination preprocessing lighting-invariant face recognition 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hu Han
    • 1
    • 2
  • Shiguang Shan
    • 1
  • Xilin Chen
    • 1
  • Shihong Lao
    • 3
  • Wen Gao
    • 4
    • 1
  1. 1.Institute of Computing Technology, CASKey Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS)BeijingChina
  2. 2.Department of Computer Science and EngineeringMichigan State UniversityEast LansingU.S.A.
  3. 3.Omron Social Solutions Co., LTD.KyotoJapan
  4. 4.Institute of Digital MediaPeking UniversityBeijingChina

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