Name
Abstract | ||
|---|---|---|
In the vehicle license plate reader system, the License Plate Recognition (LPR) is designed based on machine vision technology without any direct human intervention. This paper presents an efficient LPR technique based on the RGB color extractor. The proposed method is capable of recognizing alphabets and numeric characters on the license plate in real-time. This technique has been tested with a large number of images in order to analyze its performance. The tested images are captured from the front and rear of the vehicles under different conditions, including different angles, luminance, and weather conditions. With the real-time test results shown in this paper, we obtain 98.5% accuracy for character extraction and 95.1% accuracy for character recognition using this technique. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/EIT.2016.7535290 | 2016 IEEE International Conference on Electro Information Technology (EIT) |
Keywords | Field | DocType |
design flow,vehicle license plate reader system,license plate recognition,LPR,RGB color extractor,machine vision technology,alphabet recognition,character recognition,image capture,intelligent transportation system,ITS | Computer vision,Character recognition,Machine vision,Computer science,Design flow,Artificial intelligence,RGB color model,Extractor,Luminance,License | Conference |
ISSN | ISBN | Citations |
2154-0357 | 978-1-4673-9986-9 | 0 |
PageRank | References | Authors |
0.34 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yonghui Jia | 1 | 0 | 0.68 |
| Thomas Gonnot | 2 | 7 | 4.17 |
| Jafar Saniie | 3 | 152 | 47.55 |