Title :
A vehicle license plate recognition system based on analysis of maximally stable extremal regions
Author :
Li, Bo ; Tian, Bin ; Yao, Qingming ; Wang, Kunfeng
Author_Institution :
State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China
Abstract :
Vehicle License Plate Recognition (VLPR) system is a core module in Intelligent Transportation Systems (ITS). In this paper, a VLPR system is proposed. Considering that license plate localization is the most important and difficult part in VLPR system, we present an effective license plate localization method based on analysis of Maximally Stable Extremal Region (MSER) features. Firstly, MSER detector is utilized to extract candidate character regions. Secondly, the exact locations of license plates are inferred according to the arrangement of characters in standard license plates. The advantage of this license plate localization method is that less assumption of environmental illumination, weather and other conditions is made. After license plate localization, we continue to recognize the license plate characters and color to complete the whole VLPR system. Finally, the proposed VLPR system is tested on our own collected dataset. The experimental results show the availability and effectiveness of our VLPR system in locating and recognizing all the explicit license plates in an image.
Keywords :
automated highways; image recognition; traffic engineering computing; ITS; MSER; VLPR; core module; environmental illumination; intelligent transportation systems; maximally stable extremal region analysis; vehicle license plate recognition system; Character recognition; Feature extraction; Histograms; Image color analysis; Image segmentation; Licenses; Lighting; intelligent transportation systems; license plate detection; license plate recognition;
Conference_Titel :
Networking, Sensing and Control (ICNSC), 2012 9th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-0388-0
DOI :
10.1109/ICNSC.2012.6204952