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Proceedings Paper

General method for inspection based on artificial vision of plan products with random or organized texture
Author(s): Jean-Louis Alexief; Naceur Kerkeni; Jean-Claude Angue
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Paper Abstract

The visual inspection is a technique of non destructive control that analyzes from pixel images conformity of a product that may present some manufacturing defects. The diversity of products to inspect implies specific method and algorithms. That leads to a dedicated design of the inspection system. Our research in the design of an inspection system based on artificial vision approaches the definition of a methodological framework for the design. We also approach aided design to determine the sequences of image processing allowing the defect detection. We propose a design framework based on the different phases leading to the conceptual model of the IAV system (inspection based on artificial vision). The aided design is envisaged under two aspects. The first one concerns products with finite dimension and determined form for which an image processing sequence planner can bring solutions. The second one concerns products with characteristic texture where it is needed to define a method for defect detection. This method will have to be applicable in many cases. Thus for inspection of plan product with texture, we propose a method based on the spectral analysis. This method uses the fact that defects produce significant modifications on the energy spectrum. It is based on the construction of an optimal spatial filter which improves contrast defect. This filter can be built automatically and/or interactively by a human operator. Several defects can be detected simultaneously by a combination of filters. To determine global image attributes, the most discriminant on the filtered image, the analysis in the main components can be used.

Paper Details

Date Published: 21 February 1996
PDF: 15 pages
Proc. SPIE 2665, Machine Vision Applications in Industrial Inspection IV, (21 February 1996); doi: 10.1117/12.232233
Show Author Affiliations
Jean-Louis Alexief, Univ. de Valenciennes et du Hainaut-Cambresis (France)
Naceur Kerkeni, Univ. de Valenciennes et du Hainaut-Cambresis (France)
Jean-Claude Angue, Univ. de Valenciennes et du Hainaut-Cambresis (France)

Published in SPIE Proceedings Vol. 2665:
Machine Vision Applications in Industrial Inspection IV
A. Ravishankar Rao; Ning Chang, Editor(s)

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