Name
Abstract | ||
|---|---|---|
This paper proposes an algorithm for real-time license plate detection. In this algorithm, the relatively easy car plate features are adopted including the simple statistical feature and Harr-like feature. The simplicity of the object features used is very helpful to real-time processing. The classifiers based on statistical features decrease the complexity of the system. They are followed by the classifiers based on Haar-like features, which makes the final classifier invariant to the brightness, color, size and position of license plates. The experimental results obtained by the proposed algorithm exhibit the encouraging performance. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11833529_20 | UIC |
Keywords | Field | DocType |
haar-like feature,real-time processing,license plate,simple statistical feature,encouraging performance,real-time license plate detection,harr-like feature,proposed algorithm exhibit,various condition,statistical feature,easy car plate feature,real time processing,real time | Vehicle identification,Computer science,Artificial intelligence,Classifier (linguistics),Distributed computing,License,Adaboost algorithm,Pattern recognition,Cascading classifiers,Speech recognition,Invariant (mathematics),Brightness,Statistical analysis | Conference |
Volume | ISSN | ISBN |
4159 | 0302-9743 | 3-540-38091-4 |
Citations | PageRank | References |
8 | 0.64 | 11 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huaifeng Zhang | 1 | 240 | 18.84 |
| Wenjing Jia | 2 | 325 | 45.08 |
| Xiangjian He | 3 | 932 | 132.03 |
| Qiang Wu | 4 | 304 | 40.42 |