Name
Abstract | ||
|---|---|---|
Automatic license plate recognition (ALPR) is the process of locating and extracting vehicles plate information from images or videos. The extracted information is essential for several everyday applications, ranging from automated payment services (e.g. parking and toll roads payment collection) to more critical applications, like border crossing security and traffic surveillance systems. Various solutions have been proposed for the ALPR problem, with many available commercial packages. However, amid plate variations from place to place, ALPR systems tend to be region-specific. There is no general solution that works effectively everywhere for every province/state or country. In this paper, we have reviewed a set of state-of-the-art ALPR methods and, compared their respective performances by testing them on a rich database of vehicles from Ontario (Canada). |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ISSPIT.2015.7394415 | ISSPIT |
Keywords | Field | DocType |
Automatic License plate recognition, ALPR, Automatic number plate recognition, ANPR, OCR | Computer vision,Character recognition,Computer science,Toll,Ranging,Artificial intelligence,Payment,Optical imaging,Payment service provider,License,Optical character recognition software | Conference |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Imran Shafiq Ahmad | 1 | 43 | 11.20 |
| Boubakeur Boufama | 2 | 162 | 22.02 |
| Pejman Habashi | 3 | 4 | 1.79 |
| William Anderson | 4 | 0 | 0.34 |
| Tarik Elamsy | 5 | 5 | 2.11 |