Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/560
DC Field | Value | Language |
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dc.contributor.author | Liew C. | en_US |
dc.contributor.author | Kim On C. | en_US |
dc.contributor.author | Alfred R. | en_US |
dc.contributor.author | Tan, Tse Guan | en_US |
dc.contributor.author | Anthony P. | en_US |
dc.date.accessioned | 2021-01-25T04:13:12Z | - |
dc.date.available | 2021-01-25T04:13:12Z | - |
dc.date.issued | 2020-06-17 | - |
dc.identifier.issn | 17426588 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/560 | - |
dc.description | Scopus | en_US |
dc.description.abstract | In this paper, the implementation of localizing and recognizing license plate in real time environment with a neural network using a mobile device is described. The neural networks used in this research are Convolutional Neural Network (CNN) and Backpropagation Feed Forward Neural Network (BPFFNN). Image processing algorithm for pre-processing, localization and segmentation is chosen based on its ability to cope with limited computational resource in mobile device. The proposed license plate localization steps include combination of Sobel edge detection method and morphological based method. Detected license plate image is segmented using connected component analysis (CCA) and bounding box method. Each cropped character is fed into CNN or BPFFNN model for character recognition process. The neural network model was pretrained using desktop computer and then later exported and implemented in Android mobile device. The experiment was conducted in a moving vehicle on selected driving routes. The results obtained showed that CNN performed better compared to BPFFNN in a real time environment. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Physics Publishing | en_US |
dc.relation.ispartof | Journal of Physics: Conference Series | en_US |
dc.subject | Convolutional neural networks | en_US |
dc.subject | Image segmentation | en_US |
dc.subject | License plates (automobile) | en_US |
dc.subject | Optical character recognition | en_US |
dc.title | Real time mobile based license plate recognition system with neural networks | en_US |
dc.type | International | en_US |
dc.relation.conference | International Conference on Telecommunication, Electronic and Computer Engineering 2019, ICTEC 2019 | en_US |
dc.identifier.doi | 10.1088/1742-6596/1502/1/012032 | - |
dc.volume | 1502 (1) | en_US |
dc.description.articleno | 012032 | en_US |
dc.date.seminarstartdate | 2019-10-22 | - |
dc.date.seminarenddate | 2019-10-24 | - |
dc.description.placeofseminar | Melaka; Malaysia | en_US |
dc.description.type | Proceeding Papers | en_US |
item.fulltext | With Fulltext | - |
item.openairetype | International | - |
item.languageiso639-1 | en | - |
item.grantfulltext | open | - |
Appears in Collections: | Faculty of Creative Technology & Heritage - Proceedings |
Files in This Item:
File | Description | Size | Format | |
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Real-time-mobile-based-license-plate-recognition-system-with-neural-networks2020Journal-of-Physics-Conference-Series.pdf | 943.18 kB | Adobe PDF | View/Open |
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