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
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;
Conference_Titel :
Circuits and Systems, 2001. ISCAS 2001. The 2001 IEEE International Symposium on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-6685-9
DOI :
10.1109/ISCAS.2001.921352
