NDLI: A Simple Method for Chinese License Plate Recognition Based on Support Vector Machine

Content Provider	IEEE Xplore Digital Library
Author	Xiaojun Chi Junyu Dong Aihua Liu Huiyu Zhou
Copyright Year	2006
Description	Author affiliation: Dept. of Comput. Sci., Ocean Univ. of China, Qingdao (Xiaojun Chi; Junyu Dong)
Abstract	We present a simple method based on support vector machine (SVM) for Chinese license plate recognition. By firstly pre-processing the input images containing license plates, a set of normalized subimages can be obtained, each of which contains a number, an English letter or a Chinese character. We then transform these subimages into vectors by simply using pixel values. In this way, we can avoid the problem of excessive dependency on feature extraction during recognition. Next, scaling and cross-validation are performed to eliminate outliers and find the best parameters for the SVM model. We use real color images captured at a motorway toll in our experiments. Be compared with previous work based on neural network, the SVM-based method produces a higher correct recognition rate. Experimental results also show the superiority of the SVM-based method when only a small number of samples are available
Sponsorship	IEEE Circuits and Syst. Soc. HKUST UESTC City Univ. of Hong Kong
Starting Page	2141
Ending Page	2145
File Size	5546197
Page Count	5
File Format	PDF
ISBN	0780395840
DOI	10.1109/ICCCAS.2006.284922
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Computer science Image segmentation Image edge detection Support vector machine classification Color Licenses Feature extraction Pattern recognition Character recognition
Content Type	Text
Resource Type	Article

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