In this thesis, we develop a method to automatically detect and recognize the vehicle license plates. By using a large number of images to study statistically several important features of the license plates, this work has developed several methods to systematically detect and recognize the license plates. In particular, these methods are used to detect edges, to locate regions with densely distributed edges, to detect region with grey color and to identify character shapes.
This work restricts its study on outdoor environment. Many environmental uncertainties such as lighting and background complexity should also be considered. By taking these factors into consideration, our algorithm can first detect the license plates. Next, our system uses a two-stage approach to recognize the characters on the plates. Most of the characters can be correctly recognized in the first stages by using conventional template-based method. However, a moment-feature based method is applied to two pairs of characters which can not be accurately classified by the template-based method.
Experimental results are given to demonstrate the effectiveness of the proposed approach. In order to improve the proposed approach in the future, this work also studies a relatively small portion of plates that can not be perfectly handled by the proposed approach.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0714106-195614 |
| Date | 14 July 2006 |
| Creators | Lin, Chia-Wei |
| Contributors | Chen-Wen Yen, Gou-Jen Wang, Cheng-Wen Ko |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0714106-195614 |
| Rights | unrestricted, Copyright information available at source archive |
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