DocumentCode
1182937
Title
Cork Parquet Quality Control Vision System Based on Texture Segmentation and Fuzzy Grammar
Author
Ferreira, Manuel J. ; Santos, Cristina ; Monteiro, João
Author_Institution
Ind. Electron. Dept., Univ. of Minho, Guimaraes
Volume
56
Issue
3
fYear
2009
fDate
3/1/2009 12:00:00 AM
Firstpage
756
Lastpage
765
Abstract
This paper presents a quality control vision system developed for the inspection of cork parquets that is already applied in the Portuguese cork industry. It is devoted specifically to the most critical quality issues: visibility of the lowest layer (BASE) on the noble layer (UPPER) and the homogeneity of this noble layer. Since these aspects are related with the texture of the raw material, the system was based on texture segmentation techniques. Features used were extracted from detail images of the wavelet transform. The classifier consists of a fuzzy grammar inference system. The segmentation procedure revealed a good performance indicated by high classification rates. Behavior in the industrial environment has been demonstrating high performance, revealing good perspectives for full spread industrialization.
Keywords
automatic optical inspection; computer vision; feature extraction; fuzzy reasoning; grammars; image classification; image segmentation; image texture; quality control; wavelet transforms; wood products; Portuguese cork industry; cork parquet inspection; cork parquet quality control vision system; feature extraction; fuzzy grammar inference system; image classification; industrial environment; texture segmentation technique; wavelet transform; Electrical equipment industry; Feature extraction; Fuzzy control; Fuzzy systems; Image segmentation; Industrial control; Inspection; Machine vision; Quality control; Raw materials; Computer vision; fuzzy grammar; industrial application; inspection system; texture segmentation;
fLanguage
English
Journal_Title
Industrial Electronics, IEEE Transactions on
Publisher
ieee
ISSN
0278-0046
Type
jour
DOI
10.1109/TIE.2008.2011619
Filename
4796889
Link To Document