Design of a Recognizing System for Vehicle's License Plates with English Characters
- Authors
- Xiong Xing; 최병재; 채석; 이문희
- Issue Date
- 2009
- Publisher
- 한국지능시스템학회
- Keywords
- License plate recognition; Image processing; Mean shift algorithm; Fuzzy ARTMAP; Neural Network
- Citation
- International Journal of Fuzzy Logic and Intelligent systems, v.9, no.3, pp 166 - 171
- Pages
- 6
- Journal Title
- International Journal of Fuzzy Logic and Intelligent systems
- Volume
- 9
- Number
- 3
- Start Page
- 166
- End Page
- 171
- URI
- https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/22995
- ISSN
- 1598-2645
- Abstract
- In recent years, video detection systems have been implemented in various infrastructures such as airport, public transportation, power generation system, water dam and so on. Recognizing moving objects in video sequence is an important problem in computer vision, with applications in several fields, such as video surveillance and target tracking. Segmentation and tracking of multiple vehicles in crowded situations is made difficult by inter-object occlusion.
In the system described in this paper, the mean shift algorithm is firstly used to filter and segment a color vehicle image in order to get candidate regions. These candidate regions are then analyzed and classified in order to decide whether a candidate region contains a license plate or not. And then some characters in the license plate is recognized by using the fuzzy ARTMAP neural network, which is a relatively new architecture of the neural network family and has the capability to learn incrementally unlike the conventional BP network. We finally design a license plate recognition system using the mean shift algorithm and fuzzy ARTMAP neural network and show its performance via some computer simulations.
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Collections - School of Electronic Engineering > 1. Journal Articles
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