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http://dx.doi.org/10.9717/kmms.2020.23.3.412

Untact Face Recognition System Based on Super-resolution in Low-Resolution Images  

Bae, Hyeon Bin (School of Electrical Electronics and Control Eng., Changwon National University)
Kwon, Oh Seol (School of Electrical Electronics and Control Eng., Changwon National University)
Publication Information
Journal of Korea Multimedia Society / v.23, no.3, 2020 , pp. 412-420 More about this Journal
Abstract
This paper proposes a performance-improving face recognition system based on a super resolution method for low-resolution images. The conventional face recognition algorithm has a rapidly decreased accuracy rate due to small image resolution by a distance. To solve the previously mentioned problem, this paper generates a super resolution images based o deep learning method. The proposed method improved feature information from low-resolution images using a super resolution method and also applied face recognition using a feature extraction and an classifier. In experiments, the proposed method improves the face recognition rate when compared to conventional methods.
Keywords
Super-resolution; Face Recognition; Feature Extraction;
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