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Sensors and Materials, Volume 31, Number 9(1) (2019)
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pp. 2771-2776
S&M1971 Letter of Special Issue
https://doi.org/10.18494/SAM.2019.2348
Published: September 9, 2019

High-performance Two-stage Face Recognition Algorithm for Reduced Illumination Effect [PDF]

Cheng-Yu Yeh, Chien-Fu Chen, and Chun-Cheng Lin

(Received February 25, 2019; Accepted July 9, 2019)

Keywords: face recognition, local binary pattern (LBP), LBP histogram (LBPH), Fisherface, principal component analysis (PCA), linear discriminant analysis (LDA)

Face recognition, which is a method of identifying a person in a digital image, is widely applied to biometric-based authentication systems. A significant decrease in recognition rate is caused by extracted features that are affected by illumination. In an attempt to resolve this problem, in this paper, we present a two-stage algorithm, namely, a local binary pattern (LBP) followed by the algorithm Fisherface. As the first step of this work, a face image is converted to an LBP, which is then projected onto a low-dimensional feature space using Fisherface for subsequent classification and recognition. As a result, the outperformance of this work is demonstrated by a recognition rate of up to 96.45%, a figure far beyond 67.97% using the LBP histogram (LBPH), 84.69% using Fisherface, and 93.09% using the support vector machine (SVM) algorithm.

Corresponding author: Chun-Cheng Lin

This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Cheng-Yu Yeh, Chien-Fu Chen, and Chun-Cheng Lin, High-performance Two-stage Face Recognition Algorithm for Reduced Illumination Effect, Sens. Mater., Vol. 31, No. 9, 2019, p. 2771-2776.