Name
Abstract | ||
|---|---|---|
This paper proposes a learning-based algorithm to detect license plates of vehicles from vehicle image database. There are three main contributions in this paper. The first contribution is to define a novel vertical edge map, which makes the image processing more effectively. The second contribution is to propose a learning-based cascade classifier composing of two kinds of sub-classifiers, which makes the system very robust. The third contribution is to experimentally estimate the parameter of scaling factor and chose an optimal one for the algorithm to seek a good balance between detection rate and processing time. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1504/IJIIDS.2007.014952 | IJIIDS |
Keywords | Field | DocType |
novel vertical edge map,processing time,learning-based cascade classifier,learning-based algorithm,main contribution,license plate,vehicle image database,detection rate,image processing,learning-based license plate detection,good balance,adaboost | Scale factor,Computer vision,Automatic image annotation,AdaBoost,Feature detection (computer vision),Pattern recognition,Computer science,Cascading classifiers,Image processing,Artificial intelligence,Digital image processing,Content-based image retrieval | Journal |
Volume | Issue | Citations |
1 | 2 | 6 |
PageRank | References | Authors |
0.59 | 24 | 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 |