Earticle

초록

영어

In this paper, we propose a new representation, called Local Min-Max Binary Pattern (LMin-MaxBP), and apply it to face recognition with single sample per class. The local appearance based methods have been successfully applied to face recognition and achieved state-of-the-art performance. The Local Binary Pattern (LBP) has been proved to be effective for image representation. The motivation for the LMin-MaxBP is to find texture information to cope with the variation due to facial expression and perspective changes as well as reducing the length of the feature vectors in LBP’s histogram to speed up the matching process. Experiments on Yale, ORL and Indian face datasets shows that the proposed approach improves the performance in the scenario of one training sample per person with significant facial expression and perspective variations with large rotation angle up to 180θ.

목차

Abstract
 1. Introduction
 2. Background Study
  2.1. Local Binary Pattern
  2.2 Face Recognition Using Local Binary Patterns
 3. Proposed Local Min-Max Binary Pattern Based Face Descriptions
 4. Experimental Results
 5. Conclusions
 References

키워드

저자

• K.Jaya Priya [ Research Scholar, Mother Teresa Women’s University ]
• R.S Rajesh [ Associate Professor, Department of Computer Science and Engineering, Manonmaniam Sundaranar University ]

참고문헌

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간행물

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• 간행물명

  International Journal of Advanced Science and Technology

• 간기

  월간

• pISSN

  2005-4238

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605