DocumentCode
1744992
Title
Defects detection and characterization by using cellular neural networks
Author
Occhipinti, L. ; Spoto, G. ; Branciforte, Marco ; Doddo, F.
Author_Institution
Soft Comput. Group, STMicroelectron. Italy, Catania, Italy
Volume
3
fYear
2001
fDate
6-9 May 2001
Firstpage
481
Abstract
In this document, a new method to detect and to characterize surface defects in mechanical parts is reported. Cellular neural networks are used as tools for the implementation of the stereoscopic vision analysis technique. Suitable applications in microscopic defect analysis (real-time processing), in various fields (e.g. aeronautics applications) are introduced, by means of the reported examples in order to validate the cellular neural networks (CNN) approach
Keywords
cellular neural nets; computer vision; flaw detection; stereo image processing; aeronautics; cellular neural networks; defects characterization; defects detection; mechanical parts; microscopic defect analysis; stereoscopic vision analysis technique; surface defects; Aerodynamics; Application specific integrated circuits; Cellular neural networks; Computer networks; Computer vision; Layout; Machine vision; Microscopy; Signal processing algorithms; Turing machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2001. ISCAS 2001. The 2001 IEEE International Symposium on
Conference_Location
Sydney, NSW
Print_ISBN
0-7803-6685-9
Type
conf
DOI
10.1109/ISCAS.2001.921352
Filename
921352
Link To Document