Na, Z, Haoting, L and Zhang, Z orcid.org/0000-0003-0204-3867 (2021) Hierarchic Clustering-Based Face Enhancement for Images Captured in Dark Fields. Electronics, 10 (8). 936. ISSN 2079-9292
Abstract
A hierarchic clustering-based enhancement is proposed to solve the luminance compensation of face recognition in the dark field. First, the face image is divided into five levels by a clustering method. Second, the results above are mapped into three hierarchies according to the histogram thresholds. A low, a middle, and a high-intensity block are found. Third, two kinds of linear transforms are performed to the high and the low-intensity blocks. Finally, a center wrap function-based enhancement is carried out. Experiment results show our method can improve both the face recognition accuracy and image quality.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | hierarchic clustering; image enhancement; dark field; image quality; face recognition |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 26 Apr 2021 12:43 |
Last Modified: | 26 Apr 2021 12:43 |
Status: | Published |
Publisher: | MDPI |
Identification Number: | 10.3390/electronics10080936 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:173127 |