DocumentCode :
467668
Title :
Research on Traffic Number Recognition Based on Neural Network and Invariant Moments
Author :
Song, Zheng-he ; Zhao, Bo ; Zhu, Zhong-xiang ; Mao, En-rong
Author_Institution :
China Agric. Univ., Beijing
Volume :
1
fYear :
2007
fDate :
19-22 Aug. 2007
Firstpage :
389
Lastpage :
393
Abstract :
Traffic number recognition is the important and essential content on license plate recognition and traffic sign recognition. A method of traffic number recognition based on the neural network and the invariant moments was proposed in this paper. Firstly, the area of the traffic number was located from the complicated image background and each number was taken by the image segmentation. Secondly, the features of each number were obtained by Hu invariant moments, which are the invariability of the translation, the ratio and the rotation, and have lower computational complexity. Finally, the traffic number was recognized by the BP neural network. Experimental results proved that the proposed method can be used for fast and efficient recognition of the traffic number with high accuracy.
Keywords :
backpropagation; image recognition; image segmentation; neural nets; traffic engineering computing; complicated image background; computational complexity; image segmentation; invariant moments; license plate recognition; neural network; traffic number recognition; traffic sign recognition; Agricultural engineering; Cybernetics; Educational institutions; Image recognition; Intelligent transportation systems; Licenses; Machine learning; Neural networks; Pattern recognition; Telecommunication traffic; Invariant moments; Neural network; Traffic number;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
Type :
conf
DOI :
10.1109/ICMLC.2007.4370175
Filename :
4370175
Link To Document :
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