Quality inspection of veneer using soft-computing methods

Stolpmann, Alexander; Angele, Jürgen and Dooley, Laurence S. (2000). Quality inspection of veneer using soft-computing methods. In: Parmee, I. C. ed. Evolutionary Design and Manufacture: Selected Papers from ACDM '00, Volume 1. London: Springer-Verlag, pp. 363–370.

DOI: https://doi.org/10.1007/978-1-4471-0519-0_30

URL: http://link.springer.com/book/10.1007/978-1-4471-0...

Abstract

This paper describes the use of a complex modular image processing system for veneer classification. An introduction into problems that arise when producing and processing veneer is given, namely flaws in the wood and faults in the final product, in this case spring boards for slatted frames.

A system has been developed that detects and classifies the faults. A line-scan camera is used for capturing the veneer images of which the features are extracted with statistical methods. The features are classified with either fuzzy clustering methods or neural networks. Additionally genetic algorithms are used for optimization purposes.

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About

• Item ORO ID
• 38058
• Item Type
• Book Section
• ISBN
• 1-85233-300-6, 978-1-85233-300-3
• Extra Information
• Selected Papers from 1st Adaptive Computing in Design and Manufacture (ACDM’00) Conference, Plymouth
• Keywords
• system optimization with genetic algorithms; neural networks and fuzzy clustering for classification; pattern recognition and image processing; application in timber industry
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Research Group
• Centre for Research in Computing (CRC)
• Copyright Holders
• © 2000 Springer-Verlag London Limited
• Related URLs
• • http://link.springer.com/chapter/10.1007...
• Depositing User
• Laurence Dooley