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Proceedings Paper

Modular system for automated surface inspection
Author(s): Dennis C. Mills
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Paper Abstract

This paper describes the application of machine vision tech n iques to the problem of surface inspection of web products, in particular high-grade painted steel strip. A different approach has been adopted to the system architecture from that found in most contemporary systems. By u tilising tradi tional machine vision techniques embodied in a combination of off-the-shelf and custom vision processing technology, a highly modular system architecture has been developed which may be applied across .a broad spectrum of inspection tasks. Each inspection module within the system consists of a standard solid-state camera, commercial digitiser and frarne­ store and one or more custorn processing boards. These custom boards are configurable spatial filters which are inexpen­ sive to replicate, allowing multiple boards optirnised for subsets of the defect space to be used. This allows the processing power required to detect defects of interest to be tailored to the application. Similarly the number of complete detection modules can be controlled in a modular fashion to meet a pplication requirements. A real-time processor coordinates the detection rnodu les ancl handles defect parameterisation and image transfer to a host computer which classifies defects and provides a user i nterface for an operator. A fully functional two-module systern has been in operation on a production steel st.rip paint.line since mid 1991.

Paper Details

Date Published: 6 May 1993
PDF: 7 pages
Proc. SPIE 1907, Machine Vision Applications in Industrial Inspection, (6 May 1993); doi: 10.1117/12.144807
Show Author Affiliations
Dennis C. Mills, CSIRO (Australia)


Published in SPIE Proceedings Vol. 1907:
Machine Vision Applications in Industrial Inspection
Frederick Y. Wu; Benjamin M. Dawson, Editor(s)

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