Name
Abstract | ||
|---|---|---|
License plate recognition usually contains three steps, namely license plate detection/localization, character segmentation and character recognition. When reading characters on a license plate one by one after license plate detection step, it is crucial to accurately segment the characters. The segmentation step may be affected by many factors such as license plate boundaries (frames). The recognition accuracy will be significantly reduced if the characters are not properly segmented. This paper presents an efficient algorithm for character segmentation on a license plate. The algorithm follows the step that detects the license plates using an AdaBoost algorithm. It is based on an efficient and accurate skew and slant correction of license plates, and works together with boundary (frame) removal of license plates. The algorithm is efficient and can be applied in real-time applications. The experiments are performed to show the accuracy of segmentation. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/MMSP.2008.4665111 | MMSP |
Keywords | Field | DocType |
license plate boundaries,license plate detection-localization,character segmentation,image segmentation,character recognition,skew correction,car license plate recognition,frame removal,slant correction,realtime applications,adaboost algorithm,classification algorithms,histograms,algorithm design and analysis,pixel | Computer vision,Histogram,Algorithm design,Pattern recognition,Computer science,Segmentation,Image segmentation,Pixel,Skew,Artificial intelligence,Statistical classification,License | Conference |
ISBN | Citations | PageRank |
978-1-4244-2295-1 | 4 | 0.48 |
References | Authors | |
5 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiangjian He | 1 | 932 | 132.03 |
| Lihong Zheng | 2 | 81 | 11.37 |
| Qiang Wu | 3 | 20 | 14.06 |
| Wenjing Jia | 4 | 325 | 45.08 |
| Bijan Samali | 5 | 17 | 5.57 |
| M. Palaniswami | 6 | 4107 | 290.84 |