DocumentCode
3424603
Title
License plate text localization using DWT and neural network
Author
Chen, Tianding
Author_Institution
Inst. of Commun. & Inf. Technol., Zhejiang Gongshang Univ., Hangzhou, China
fYear
2009
fDate
17-19 Aug. 2009
Firstpage
73
Lastpage
77
Abstract
The license plate text automatic localization is one of the important research subjects in the intelligent transportation system. License plate texts provide highly condensed information about the contents of images. It proposes a license plate text localization method using discrete wavelet transform (DWT) and neural network. Because the DWT coefficients provide important information of text regions, this paper employs those coefficients and several image processing techniques to preliminarily locate candidate license plate text regions. Then the morphological dilation operation and the neural network are employed to raise the precision rate of the location for license plate text. The objective of the research is to increase the recognition rate of license plates and to improve the success rate of license plate locating. According to the experimental results, the proposed method can successfully locate text region from complex environment. It demonstrates the feasibility of this system and achieves 96% of the correct plate location rate.
Keywords
automated highways; discrete wavelet transforms; image processing; neural nets; text analysis; discrete wavelet transform; image processing techniques; intelligent transportation system; license plate text automatic localization method; morphological dilation operation; neural network; Character recognition; Costs; Discrete wavelet transforms; Image recognition; Intelligent transportation systems; Licenses; Neural networks; Radiofrequency identification; Text recognition; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2009, GRC '09. IEEE International Conference on
Conference_Location
Nanchang
Print_ISBN
978-1-4244-4830-2
Type
conf
DOI
10.1109/GRC.2009.5255154
Filename
5255154
Link To Document