DocumentCode :
2235737
Title :
Image Defect Recognition Based on Rough Set
Author :
Zhe Liu ; Xiao-jiu Li ; Liu Zhe
Author_Institution :
Tianjin Polytech. Univ., Tianjin
fYear :
2009
fDate :
24-25 April 2009
Firstpage :
263
Lastpage :
266
Abstract :
This paper applies rough set theory to recognition system for image defect, and designs a decision algorithm on rough set suitable for image defect recognition. Firstly, the image is made regionalization and sequential discrete set is proposed, the continuous attributes of image is discretized. Then the decision table model on discrete condition attributes and decision attributes is constructed. Further the condition attributes significance function and reduction algorithm is given. A novel approach for decision rule analysis and rough set recognition is proposed. Finally, this paper takes the example for fabric defect recognition to validate these algorithms. The result shows the rough set algorithm is effective for image defect recognition with less calculation and fast speed.
Keywords :
data mining; decision tables; image recognition; rough set theory; attribute reduction algorithm; attributes significance function; decision algorithm; decision table model; image defect recognition; image regionalization; rough set theory; sequential discrete set; Algorithm design and analysis; Clustering algorithms; Filtering algorithms; Fourier transforms; Frequency domain analysis; Image recognition; Information systems; Machine learning; Pattern recognition; Set theory; Defect; Image; Recognition; Rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial and Information Systems, 2009. IIS '09. International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-3618-7
Type :
conf
DOI :
10.1109/IIS.2009.109
Filename :
5116349
Link To Document :
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