DocumentCode :
1598468
Title :
The recognition of electronic component´s printed marks based on rough set
Author :
Guosen ; Wang, Yan ; Wu, Zhi-cheng
Author_Institution :
Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Volume :
2
fYear :
2004
Firstpage :
1116
Abstract :
Rough set (RS) developed by Professor Z. Pawlak in 1982 has been applied successfully in such fields as machine learning, data mining, intelligent data analyzing, control algorithm acquiring, etc. In our paper, we apply this theory to recognize characters printed on the surface of electronic component. According to the properties of these characters, we propose a new method based on mathematical morphology to extract feature. Here, we propose a new algorithm to generate rules from decision table, and classify character based on the prior probability derived from such rule set In order to reduce the complexity further, we design a flow to pick train samples. The result of experiment shows our methods are useful and efficiency.
Keywords :
character recognition; decision tables; feature extraction; image sampling; knowledge acquisition; learning (artificial intelligence); mathematical morphology; printed circuits; rough set theory; decision table; electronic component; feature extraction; mathematical morphology; printed character recognition; probability; rough set theory; rule generation; train sample; Algorithm design and analysis; Character recognition; Data analysis; Data mining; Intelligent control; Learning systems; Machine learning; Machine learning algorithms; Rough surfaces; Surface roughness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Technology, 2004. IEEE ICIT '04. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8662-0
Type :
conf
DOI :
10.1109/ICIT.2004.1490234
Filename :
1490234
Link To Document :
بازگشت