Small Face Recognition Algorithm Based on Super-resolution Reconstruction

Aiming at the problem of low recognition rate caused by the lack of effective identity information in small-scale face images with low resolution, this small face recognition algorithm based on super-resolution reconstruction is proposed. The algorithm first performs super-resolution reconstruction...

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Bibliographic Details
Main Authors: LI Jing-yu, CHENG Wei-yue, LI Zi-xiang, LIN Ke-zheng
Format: Article
Language:zho
Published: Harbin University of Science and Technology Publications 2022-06-01
Series:Journal of Harbin University of Science and Technology
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Online Access:https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2095
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Summary:Aiming at the problem of low recognition rate caused by the lack of effective identity information in small-scale face images with low resolution, this small face recognition algorithm based on super-resolution reconstruction is proposed. The algorithm first performs super-resolution reconstruction on the collected low-resolution face images, and uses the method of detail enhancement to restore high-frequency information such as facial contour information and texture details of the image, and then uses an improved densely connected network to do feature extraction and image recognition. Experimental results show that this method is aimed at small-scale face images, and is superior to other face recognition algorithms in image recognition rate, and can effectively solve the problem of low recognition rate of small faces in real environments.
ISSN:1007-2683