A Robust Method for Partially Occluded Face Recognition

Due to the wide application of face recognition (FR) in information security, surveillance, access control and others, it has received significantly increased attention from both the academic and industrial communities during the past several decades. However, partial face occlusion is one of the mo...

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Bibliographic Details
Published in:KSII transactions on Internet and information systems 2015, 9(7), , pp.2667-2682
Main Authors: Xu, Wenkai, Lee, Suk-Hwan, Lee, Eung-Joo
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Biometry
Engineering research
Methods
Safety and security measures
컴퓨터학
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Summary:Due to the wide application of face recognition (FR) in information security, surveillance, access control and others, it has received significantly increased attention from both the academic and industrial communities during the past several decades. However, partial face occlusion is one of the most challenging problems in face recognition issue. In this paper, a novel method based on linear regression-based classification (LRC) algorithm is proposed to address this problem. After all images are downsampled and divided into several blocks, we exploit the evaluator of each block to determine the clear blocks of the test face image by using linear regression technique. Then, the remained uncontaminated blocks are utilized to partial occluded face recognition issue. Furthermore, an improved Distance-based Evidence Fusion approach is proposed to decide in favor of the class with average value of corresponding minimum distance. Since this occlusion removing process uses a simple linear regression approach, the completely computational cost approximately equals to LRC and much lower than sparse representation-based classification (SRC) and extended-SRC (eSRC). Based on the experimental results on both AR face database and extended Yale B face database, it demonstrates the effectiveness of the proposed method on issue of partial occluded face recognition and the performance is satisfactory. Through the comparison with the conventional methods (eigenface+NN, fisherfaces+NN) and the state-of-the-art methods (LRC, SRC and eSRC), the proposed method shows better performance and robustness. Keywords: Face recognition, partial occlusion, sub-images, LRC
ISSN:1976-7277
1976-7277
DOI:10.3837/tiis.2015.07.019