NDLI: Car license plate recognition based on the combination of principal components analysis and radial basis function networks

Content Provider	IEEE Xplore Digital Library
Author	Cheng, Y. Lu, J. Yahagi, T.
Copyright Year	2004
Description	Author affiliation: Graduate Sch. of Sci. & Technol., Chiba Univ., Japan (Cheng, Y.; Lu, J.; Yahagi, T.)
Abstract	This paper proposes a car license plate recognition system. First, an approach based on histogram analysis method together with Hough transform is presented for segmentation. It is robust to car plate inclination within 15 degree. Subsequently, in the recognition phase, we use principle components analysis to extract the feature of input images and then feed to neural networks with radial basis function networks is used for symbols recognition. Experimental results show that the PCA method proposed reduces the dimension of image effectively and the recognition performance using RBF networks with 98% is better than back-propagation (BP) with 93%.
Starting Page	1455
Ending Page	1458
File Size	638453
Page Count	4
File Format	PDF
ISBN	0780384067
DOI	10.1109/ICOSP.2004.1441601
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-08-31
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Licenses Principal component analysis Radial basis function networks Image recognition Histograms Image segmentation Robustness Image analysis Feature extraction Feeds
Content Type	Text
Resource Type	Article

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Car license plate recognition based on the combination of principal components analysis and radial basis function networks