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http://dx.doi.org/10.6109/jkiice.2017.21.9.1674

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

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)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.21, no.9, 2017 , pp. 1674-1680 More about this Journal
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.
Keywords
Embedded system; signal processing; face authentication; local binary pattern; Raspberry PI;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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