HD Qatari ANPR system
| Author | Hommos, Omar |
| Author | Al-Qahtani, Abdulhadi |
| Author | Al-Zawqari, Ali Farhat Ali |
| Author | Bensaali, Faycal |
| Author | Amira,Abbes |
| Author | Zhai, Xiaojun |
| Available date | 2021-03-18T10:15:10Z |
| Publication Date | 2016 |
| Publication Name | 2016 International Conference on Industrial Informatics and Computer Systems, CIICS 2016 |
| Resource | Scopus |
| Abstract | Recently, Automatic Number Plate Recognition (ANPR) systems have become widely used in safety, security, and commercial aspects. The whole ANPR system is based on three main stages: Number Plate Localization (NPL), Character Segmentation (CS), and Optical Character Recognition (OCR). In recent years, to provide better recognition rate, High Definition (HD) cameras have started to be used. However, most known techniques for standard definition are not suitable for real-time HD image processing due to the computationally intensive cost of localizing the number plate. In this paper, algorithms to implement the three main stages of a high definition ANPR system for Qatari number plates are presented. The algorithms have been tested using MATLAB and two databases as a proof of concept. Implementation results have shown that the system is able to process one HD image in 61 ms, with an accuracy of 98.0% in NPL, 99.75% per character in CS, and 99.5% in OCR. 2016 IEEE. |
| Language | en |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Subject | ANPR Character Segmentation Number Plate Localization Optical Character Recognition |
| Type | Conference |
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Electrical Engineering [2811 items ]