Name
Abstract | ||
|---|---|---|
Continual improvements in technology have meant that conventional manual methods of toll collection have been supplanted by electronic toll collection (ETC). ETC has been implemented in many jurisdictions. However, numerous motorists attempt to evade detection by concealing or changing their license plates. To identify such motorists, we propose a method to identify vehicles without depending on license plate data. In contrast to conventional methods for recognizing license plates, vehicles in the present study were matched using information on their appearance. An aligned chamfer history image (ACHI) with a standardization scheme using a speeded-up robust features descriptor was constructed to identify vehicles sans license plate data. Regardless of the vehicle image in the database has only captured a part of vehicle body. Our novel ACHI scheme allows a comprehensive vehicle model to be constructed on the basis of a training database. The robustness of our novel scheme for toll road ETC use was validated by the results of the present study. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s11042-019-7396-8 | Multimedia Tools and Applications |
Keywords | Field | DocType |
Chamfer history image, Object tracking, Object modeling, Object verification, Vehicle verification | Computer vision,Electronic toll collection,Toll,Computer science,Chamfer,Object model,Robustness (computer science),Video tracking,Artificial intelligence,Toll road,License | Journal |
Volume | Issue | ISSN |
78 | 20 | 1380-7501 |
Citations | PageRank | References |
0 | 0.34 | 18 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huang-Chia Shih | 1 | 187 | 21.98 |
| Hao-you Wang | 2 | 4 | 1.12 |