DocumentCode :
1562512
Title :
A method based on rough set and SOFM neural network for the car´s plate character recognition
Author :
Fang, Min ; Liang, Chaojun ; Zhao, Xiaoxia
Author_Institution :
Sch. of Electr. Eng. & Autom., Hefei Univ. of Technol., China
Volume :
5
fYear :
2004
Firstpage :
4037
Abstract :
Combining rough set theory and self-organizing feature map (SOFM) neural network, a method was presented for the car´s plate character recognition. The features of the training samples were extracted to build up the decision table; the discretization algorithm of decision attributes was proposed based on the clustering ability of SOFM network; the rough set theory was applied to reduce the decision table. Finally, the reduced decision attributes were used to construct neural network recognizing machine. The method can reduce the numbers of attributes in the decision table, simplify the structure of neural network and improve the ability of generality. The experiment results of the car´s plate character recognition show that the algorithms are practical and effective.
Keywords :
automobiles; character recognition; decision tables; pattern clustering; rough set theory; self-organising feature maps; car plate character recognition; clustering ability; decision attributes; decision table; discretization algorithm; feature extraction; neural network recognizing machine; rough set theory; self organizing feature map neural network; Automation; Chaos; Character recognition; Clustering algorithms; Electronic mail; Neural networks; Set theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
Type :
conf
DOI :
10.1109/WCICA.2004.1342258
Filename :
1342258
Link To Document :
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