- Title
- Improving licence plate detection using generative adversarial networks
- Creator
- Boby, Alden, Brown, Dane L
- Subject
- To be catalogued
- Date
- 2022
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/464145
- Identifier
- vital:76480
- Identifier
- xlink:href="https://link.springer.com/chapter/10.1007/978-3-031-04881-4_47"
- Description
- The information on a licence plate is used for traffic law enforcement, access control, surveillance and parking lot management. Existing li-cence plate recognition systems work with clear images taken under controlled conditions. In real-world licence plate recognition scenarios, images are not as straightforward as the ‘toy’ datasets used to bench-mark existing systems. Real-world data is often noisy as it may contain occlusion and poor lighting, obscuring the information on a licence plate. Cleaning input data before using it for licence plate recognition is a complex problem, and existing literature addressing the issue is still limited. This paper uses two deep learning techniques to improve li-cence plate visibility towards more accurate licence plate recognition. A one-stage object detector popularly known as YOLO is implemented for locating licence plates under challenging situations. Super-resolution generative adversarial networks are considered for image upscaling and reconstruction to improve the clarity of low-quality input. The main focus involves training these systems on datasets that include difficult to detect licence plates, enabling better performance in unfavourable conditions and environments.
- Format
- computer, online resource, application/pdf, 1 online resource (12 pages), pdf
- Publisher
- SpringerLink
- Language
- English
- Relation
- Iberian Conference on Pattern Recognition and Image Analysis, Boby, A. and Brown, D., 2022, April. Improving licence plate detection using generative adversarial networks. In Iberian Conference on Pattern Recognition and Image Analysis (pp. 588-601). Cham: Springer International Publishing, Iberian Conference on Pattern Recognition and Image Analysis p. 588 2022 1611-3349
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the SpringerLink Terms of Use Statement ( https://link.springer.com/termsandconditions)
- Rights
- Closed Access
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- Visitors: 128
- Downloads: 7
Collections
Brown, Dane Lesley (Associate Prof)
SDG 09. Industry, Innovation and Infrastructure
RU Department of Computer Science
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Improving licence plate detection using generative adversarial networks.pdf | 700 KB | Adobe Acrobat PDF | View Details Download |