NDLI: Design of license plate recognition system based on the adaptive algorithm

Content Provider	IEEE Xplore Digital Library
Author	Liu Ying Li Nannan
Copyright Year	2008
Description	Author affiliation: Dept. of Appl. Math., Liaoning Provincial Coll. of Commun., Shenyang (Liu Ying)
Abstract	A new recognition system for the car license plate is designed in view of the low accuracy and the lost time of the identification program in a complex environment, such as low and varying light or strange noisy. The algorithm is composed of five steps: the image preprocessing, the position and segmentation of the license plate, the characters cutting, the feature extraction and the character recognition. It extracts the features based on the multi-scale wavelet. The recognition for characters used the RBF neural network. The new adaptive strategy for raising the speed of recognition is proposed by decreasing the number of some existing hidden layers and the dimension of some features from the wavelet. The experiment results of the actual images show that the average recognition rate can reach more than 92% and the average recognition spend is less 0.11 s than the existing RBF algorithm.
Starting Page	2818
Ending Page	2821
File Size	209222
Page Count	4
File Format	PDF
ISBN	9781424425020
DOI	10.1109/ICAL.2008.4636655
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-01
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms Image recognition Artificial neural networks Transforms license plate recognition wavelet transform Feature extraction Eigenvalues and eigenfunctions Character recognition characters cutting neural network
Content Type	Text
Resource Type	Article

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