Earticle

초록

영어

In this paper, we have proposed an optimized sparse representation algorithm based on Log-Gabor (Sparse Representation-based Classification Based on Log-Gabor, Log-GSRC), which applies local features information of samples to the sparse representation method. Actually, SRC (Sparse Representation-based Classification) is using a linear correlation between the samples of one class which can be assumed that these samples exist in a subspace, and also can be linear represented with each other. It is a global representation and it ignores the local features information of the samples, while in the case of there are a smaller number of training samples per class, SRC will obtain an inaccurate classification result which may correspond to one and more classes in the process of sparse decomposition. However, the Log-GSRC combines global and local features information of the samples and also improves the robustness of SRC. The experimental results clearly showed that Log-GSRC has much better performance than SRC and also has much higher recognition rates than SRC in face recognition.

목차

Abstract
 1. Introduction
 2. Sparse Representation-based Classification (SRC)
 3. Gabor filters and Log-Gabor filters Theory
  3.1. Gabor Filters
  3.2. Log-Gabor Filters
  3.3 Log-Gabor Features of Face Image
 4. Sparse Representation-based Classification Based on Log-Gabor (Log-GSRC)
 5. Experimental Results
  5.1. ORL Database
  5.2. AR Database
 6. Conclusions
 Acknowledgements
 References

키워드

저자

• Bin Wang [ University of Science and Technology of China Hefei 230027, P.R. China Center for Biomimetic Sensing and Control Research, Institute of Intelligent Machine, Chinese Academy of Science, Hefei, Anhui Province, P. R. China ]
• Dawen Ding [ University of Science and Technology of China Hefei 230027, P.R. China Center for Biomimetic Sensing and Control Research, Institute of Intelligent Machine, Chinese Academy of Science, Hefei, Anhui Province, P. R. China ]
• Jing Yang [ University of Science and Technology of China Hefei 230027, P.R. China Center for Biomimetic Sensing and Control Research, Institute of Intelligent Machine, Chinese Academy of Science, Hefei, Anhui Province, P. R. China ]
• Bin Kong [ University of Science and Technology of China Hefei 230027, P.R. China Center for Biomimetic Sensing and Control Research, Institute of Intelligent Machine, Chinese Academy of Science, Hefei, Anhui Province, P. R. China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605