Deep learning development for automatic license plate detection with text extraction capability
Vehicle identification and tracking are essential in traffic surveillance systems, which prioritize safety and efficiency. Security personnel still manually observe medium-sized structures. Security officers physically record license plate numbers after visually examining passing automobiles. This p...
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| Format: | Conference or Workshop Item |
| Language: | en |
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2024
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| Online Access: | http://eprints.uthm.edu.my/12226/1/P17104_934ac0017b91a0d6728a42521ab2f435.pdf%2020.pdf http://eprints.uthm.edu.my/12226/ https://doi.org/10.30880/aitcs.2024.05.01.066 |
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| author | Murshed Dokhan, Sabri Nasser Hussein Nureize Arbaiy, Nureize Arbaiy |
| author_facet | Murshed Dokhan, Sabri Nasser Hussein Nureize Arbaiy, Nureize Arbaiy |
| author_sort | Murshed Dokhan, Sabri Nasser Hussein |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Vehicle identification and tracking are essential in traffic surveillance systems, which prioritize safety and efficiency. Security personnel still manually observe medium-sized structures. Security officers physically record license plate numbers after visually examining passing automobiles. This process is time-consuming and error prone. This project aims to create a web-based deep learning system for automated license plate identification with text extraction at UTHM, Malaysia. A variety of car license plates will train the system. A convolutional neural network will immediately detect and interpret license plate text. The user may submit a vehicle photo to the online interface, and the system will recognize the license plate number and return a picture with the highlighted plate. The system will be tested on a set of concepts using accuracy and precision criteria. Traffic management and vehicle identification might employ the created technology |
| format | Conference or Workshop Item |
| id | my.uthm.eprints-12226 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2024 |
| record_format | eprints |
| spelling | my.uthm.eprints-122262025-04-29T02:40:03Z http://eprints.uthm.edu.my/12226/ Deep learning development for automatic license plate detection with text extraction capability Murshed Dokhan, Sabri Nasser Hussein Nureize Arbaiy, Nureize Arbaiy QA Mathematics Vehicle identification and tracking are essential in traffic surveillance systems, which prioritize safety and efficiency. Security personnel still manually observe medium-sized structures. Security officers physically record license plate numbers after visually examining passing automobiles. This process is time-consuming and error prone. This project aims to create a web-based deep learning system for automated license plate identification with text extraction at UTHM, Malaysia. A variety of car license plates will train the system. A convolutional neural network will immediately detect and interpret license plate text. The user may submit a vehicle photo to the online interface, and the system will recognize the license plate number and return a picture with the highlighted plate. The system will be tested on a set of concepts using accuracy and precision criteria. Traffic management and vehicle identification might employ the created technology 2024-08-30 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/12226/1/P17104_934ac0017b91a0d6728a42521ab2f435.pdf%2020.pdf Murshed Dokhan, Sabri Nasser Hussein and Nureize Arbaiy, Nureize Arbaiy (2024) Deep learning development for automatic license plate detection with text extraction capability. In: Applied Information Technology And Computer Science. https://doi.org/10.30880/aitcs.2024.05.01.066 |
| spellingShingle | QA Mathematics Murshed Dokhan, Sabri Nasser Hussein Nureize Arbaiy, Nureize Arbaiy Deep learning development for automatic license plate detection with text extraction capability |
| title | Deep learning development for automatic license plate detection with text extraction capability |
| title_full | Deep learning development for automatic license plate detection with text extraction capability |
| title_fullStr | Deep learning development for automatic license plate detection with text extraction capability |
| title_full_unstemmed | Deep learning development for automatic license plate detection with text extraction capability |
| title_short | Deep learning development for automatic license plate detection with text extraction capability |
| title_sort | deep learning development for automatic license plate detection with text extraction capability |
| topic | QA Mathematics |
| url | http://eprints.uthm.edu.my/12226/1/P17104_934ac0017b91a0d6728a42521ab2f435.pdf%2020.pdf http://eprints.uthm.edu.my/12226/ https://doi.org/10.30880/aitcs.2024.05.01.066 |
| url_provider | http://eprints.uthm.edu.my/ |