Face Recognition Based on Non-Subsampled Contourlet Transform and Multi-order Fusion Binary Patterns

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• 作者：Yao Deng (21)
  Weifeng Li (21)
  Zhenhua Guo (21)
  Youbin Chen (21)
  
• 关键词：Non ; subsampled contourlet transform (NSCT) ; multi ; order fusion binary patterns (MFBP) ; block ; based Fisher linear discriminant (BFLD) ; face recognition
• 刊名：Lecture Notes in Computer Science
• 出版年：2013
• 出版时间：2013
• 年：2013
• 卷：8261
• 期：1
• 页码：529-537
• 全文大小：414KB
• 作者单位：Yao Deng (21)
  Weifeng Li (21)
  Zhenhua Guo (21)
  Youbin Chen (21)
  
  21. Graduate School at Shenzhen, Tsinghua University, China
  
• ISSN：1611-3349

文摘

In this paper, we propose a novel face representation approach based on Non-subsampled Contourlet Transform (NSCT) and Multi-order Fusion Binary Patterns (MFBP). NSCT, which is a newly developed multi-resolution analysis tool in image denoising and enhancement, can be used to effectively capture image features of both geometrical structure and directional texture information. Due to the ability of extracting multi-order derivatives of texture patterns, the MFBP is applied on the NSCT coefficient images to achieve enhanced face representation. Furthermore, Block-based Fisher Linear Discriminant (BFLD) feature selection and weight scheme based on Fisher Separation Criteria (FSC) are chosen to further improve discriminative power of the proposed face representation. The experiments on public FERET database demonstrate that our approach outperforms many of the state-of-the-art methods.