Hierarchic Clustering-Based Face Enhancement for Images Captured in Dark Fields
| Autor: | Zhiqiang Zhang, Na Zheng, Haoting Liu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Computer Networks and Communications
Computer science Image quality ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION lcsh:TK7800-8360 Facial recognition system Luminance Image (mathematics) Histogram image quality image enhancement Electrical and Electronic Engineering Cluster analysis dark field Block (data storage) business.industry lcsh:Electronics Pattern recognition Hardware and Architecture Control and Systems Engineering Face (geometry) Signal Processing hierarchic clustering Artificial intelligence business face recognition |
| Zdroj: | Electronics Volume 10 Issue 8 Electronics, Vol 10, Iss 936, p 936 (2021) |
| ISSN: | 2079-9292 |
| DOI: | 10.3390/electronics10080936 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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