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Implementation of a Face Authentication Embedded System Using High-dimensional Local Binary Pattern Descriptor and Joint Bayesian Algorithm

고차원 국부이진패턴과 결합베이시안 알고리즘을 이용한 얼굴인증 임베디드 시스템 구현

  • Kim, Dongju (Information Research Lab., Pohang University of Science and Technology) ;
  • Lee, Seungik (Department of Smart Software, Yonam Institute of Technology) ;
  • Kang, Seog Geun (Department of Semiconductor Engineering, Gyeongsang National University)
  • Received : 2017.07.31
  • Accepted : 2017.08.16
  • Published : 2017.09.30

Abstract

In this paper, an embedded system for face authentication, which exploits high-dimensional local binary pattern (LBP) descriptor and joint Bayesian algorithm, is proposed. We also present a feasible embedded system for the proposed algorithm implemented with a Raspberry Pi 3 model B. Computer simulation for performance evaluation of the presented face authentication algorithm is carried out using a face database of 500 persons. The face data of a person consist of 2 images, one for training and the other for test. As performance measures, we exploit score distribution and face authentication time with respect to the dimensions of principal component analysis (PCA). As a result, it is confirmed that an embedded system having a good face authentication performance can be implemented with a relatively low cost under an optimized embedded environment.

본 논문에서는 고차원 국부이진패턴과 결합베이시안 알고리즘을 이용한 얼굴인증 임베디드 시스템을 제안한다. 또한, 제안된 알고리즘에 대한 임베디드 시스템을 라즈베리파이 3을 이용하여 구현한 결과를 제시한다. 제안된 얼굴인증 알고리즘에 대한 평가는 500명의 얼굴 데이터가 저장된 데이터베이스를 이용하여 수행하였다. 여기서 각각의 얼굴 데이터는 학습용과 테스트용 이미지로 구성하였다. 성능평가를 위한 척도로는 주성분분석법의 차원에 따른 스코어 분포와 얼굴인증 시간을 이용하였다. 그 결과, 최적화된 임베디드 환경에서 우수한 얼굴인증 성능을 가지는 임베디드 시스템을 상대적으로 저렴한 비용으로 구현할 수 있음을 확인하였다.

Keywords

References

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