DocumentCode :
240001
Title :
Automatic Ontario license plate recognition using local normalization and intelligent character classification
Author :
Yazdian, Nazanin ; Yun Tie ; Venetsanopoulos, Anastasios ; Ling Guan
Author_Institution :
Electr. Eng. Dept., Ryerson Univ., Toronto, ON, Canada
fYear :
2014
fDate :
4-7 May 2014
Firstpage :
1
Lastpage :
6
Abstract :
The purpose of this paper is to introduce a robust method to address the problem of license plate recognition of Ontario on the basis of an illumination compensation technique and intelligent character recognition algorithm. To foster our aim, we firstly frame the input video from into stream of images the database. We then apply our pre-processing and local normalization algorithms to remove the noise and variance of lighting conditions. The image registration is utilized for the plate segmentation and feature construction. The improved cross correlation and D-Isomap analysis are used separately for final stage in character recognition. The experimental results demonstrate a significant performance improvement achieved by the proposed methods.
Keywords :
character recognition; compensation; image classification; image denoising; image registration; image segmentation; traffic engineering computing; video signal processing; D-Isomap analysis; automatic Ontario license plate recognition; cross correlation; feature construction; illumination compensation technique; image registration; input video frame; intelligent character classification; intelligent character recognition algorithm; lighting conditions; local normalization algorithms; noise removal; plate segmentation; Adaptive optics; Image segmentation; Integrated optics; Operating systems; Optical imaging; Testing; Discriminative Isomap; illumination compensation; license plate recognition; local normalization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2014 IEEE 27th Canadian Conference on
Conference_Location :
Toronto, ON
ISSN :
0840-7789
Print_ISBN :
978-1-4799-3099-9
Type :
conf
DOI :
10.1109/CCECE.2014.6900979
Filename :
6900979
Link To Document :
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