License Plate Recognition using Multi-cluster and Multilayer Neural Networks
Vehicle license plat recognition has been a much studied research area in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is rather different for each country. In this paper, an automatic license plate recognit...
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| Format: | Article |
| Language: | en |
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IEEE
2006
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| Online Access: | http://eprints.utm.my/1645/1/marzuki06_Plate_Recognition.pdf http://eprints.utm.my/1645/ http://ieeexplore.ieee.org |
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| _version_ | 1845470511718465536 |
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| author | Sheikh Abdullah, Siti Norul Huda Khalid, Marzuki Yusof, Rubiyah |
| author_facet | Sheikh Abdullah, Siti Norul Huda Khalid, Marzuki Yusof, Rubiyah |
| author_sort | Sheikh Abdullah, Siti Norul Huda |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Vehicle license plat recognition has been a much studied research area in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is rather different for each country. In this paper, an automatic license plate recognition system is proposed for Malaysian vehicles with standard license plates based on image processing, feature extraction and neural networks. The image-processing library is developed in-house which we referred to as Vision System Development Platform (VSDP). Multi-Cluster approach is applied to locate the license plate at the right position while Kirsch Edge feature extraction technique is used to extract features from the license plates characters which are then used as inputs
to the neural network classifier. The neural network
model is the standard multilayered perceptron trained
using the back-propagation algorithm. The prototyped
system has an accuracy of more than 91%, however,
suggestions to further improve the system are dtscussed
in this paper based on the analysis of the error. |
| format | Article |
| id | my.utm.eprints-1645 |
| institution | Universiti Teknologi Malaysia |
| language | en |
| publishDate | 2006 |
| publisher | IEEE |
| record_format | eprints |
| spelling | my.utm.eprints-16452010-06-01T02:56:49Z http://eprints.utm.my/1645/ License Plate Recognition using Multi-cluster and Multilayer Neural Networks Sheikh Abdullah, Siti Norul Huda Khalid, Marzuki Yusof, Rubiyah TK Electrical engineering. Electronics Nuclear engineering Vehicle license plat recognition has been a much studied research area in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is rather different for each country. In this paper, an automatic license plate recognition system is proposed for Malaysian vehicles with standard license plates based on image processing, feature extraction and neural networks. The image-processing library is developed in-house which we referred to as Vision System Development Platform (VSDP). Multi-Cluster approach is applied to locate the license plate at the right position while Kirsch Edge feature extraction technique is used to extract features from the license plates characters which are then used as inputs to the neural network classifier. The neural network model is the standard multilayered perceptron trained using the back-propagation algorithm. The prototyped system has an accuracy of more than 91%, however, suggestions to further improve the system are dtscussed in this paper based on the analysis of the error. IEEE 2006-04-24 Article PeerReviewed application/pdf en http://eprints.utm.my/1645/1/marzuki06_Plate_Recognition.pdf Sheikh Abdullah, Siti Norul Huda and Khalid, Marzuki and Yusof, Rubiyah (2006) License Plate Recognition using Multi-cluster and Multilayer Neural Networks. 2nd International Conference on Information and Communication Technologies , 1 . pp. 1818-1823. http://ieeexplore.ieee.org |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Sheikh Abdullah, Siti Norul Huda Khalid, Marzuki Yusof, Rubiyah License Plate Recognition using Multi-cluster and Multilayer Neural Networks |
| title | License Plate Recognition using Multi-cluster and Multilayer Neural Networks |
| title_full | License Plate Recognition using Multi-cluster and Multilayer Neural Networks |
| title_fullStr | License Plate Recognition using Multi-cluster and Multilayer Neural Networks |
| title_full_unstemmed | License Plate Recognition using Multi-cluster and Multilayer Neural Networks |
| title_short | License Plate Recognition using Multi-cluster and Multilayer Neural Networks |
| title_sort | license plate recognition using multi-cluster and multilayer neural networks |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utm.my/1645/1/marzuki06_Plate_Recognition.pdf http://eprints.utm.my/1645/ http://ieeexplore.ieee.org |
| url_provider | http://eprints.utm.my/ |