Earticle

초록

영어

In this paper, we present a novel face recognition method called Multi-scale block Center-Symmetric Local Binary Pattern (MCS-LBP). The face recognition process mainly consists of three phase: face representation, feature extraction, and classification. However, the most important phase is extraction, in which unique features of the face image are extracted. The Center-Symmetric Local Binary Pattern (CS-LBP) feature can be viewed as a combination of texture-based features and gradient-based features. However, it has less dimensional area; the bit-wise comparison made between two single pixel values is significantly affected by noise and sensitive to image translation and rotation. To address this problem, we present a modified feature called MCS-LBP. Instead of individual pixels, in the modified CS-LBP, the comparison is performed based on average gray values of sub-regions. Hence, it provides more complete representation than the Local Binary Pattern (LBP) and CS-LBP operator. Experiments demonstrate the proposed method.

목차

Abstract
 1. Introduction
 2. The Proposed Method
  2.1 Local Binary Patterns (LBP)
  2.2 Center-Symmetric Local Binary Patterns (CS-LBP)
  2.3 Multi-Scale Block Centre-Symmetric Local Binary Pattern (MCS-LBP)
  2.4 Modified MCS-LBP Algorithm
  2.5 Chi-Square Distance (X2)
 3. Experimental Results
  3.1 Face Description with MCS-LBP
  3.2 Database
 4. Conclusion
 Acknowledgments
 References

키워드

저자

• Anusha Alapati [ Dong-A University, Dept. of Electronics Engineering, 37 Nakdong-daero 550 beon-gil Saha-gu, Busan, Korea ]
• Dae-Seong Kang [ Dong-A University, Dept. of Electronics Engineering, 37 Nakdong-daero 550 beon-gil Saha-gu, Busan, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605