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Proceedings Paper

A SOM-based system for web surface inspection
Author(s): Jukka Iivarinen; Jussi Pakkanen; Juhani Rauhamaa
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Paper Abstract

In this paper a system for web surface inspection is described. It has three parts: an image acquisition part, a defect detection part, and a defect classification part. The self-organizing maps (SOMs) are used both in defect detection and in defect classification which makes the system adaptable to different types of surfaces and defects. Our main focus is on defect classification where a generic content-based image retrieval (CBIR) system called PicSOM is utilized. The PicSOM uses tree-structured SOMs (TS-SOMs) and relevance feedback. It is trained with the feature sets of the defects in the database. For defect description, features from the MPEG-7 standard (the homogeneous texture, the color structure, and the edge histogram) are used and for the shape description our own shape feature set is applied. Results indicate that the system works with a high level of success.

Paper Details

Date Published: 3 May 2004
PDF: 10 pages
Proc. SPIE 5303, Machine Vision Applications in Industrial Inspection XII, (3 May 2004); doi: 10.1117/12.526617
Show Author Affiliations
Jukka Iivarinen, Helsinki Univ. of Technology (Finland)
Jussi Pakkanen, Helsinki Univ. of Technology (Finland)
Juhani Rauhamaa, ABB Oy (Finland)


Published in SPIE Proceedings Vol. 5303:
Machine Vision Applications in Industrial Inspection XII
Jeffery R. Price; Fabrice Meriaudeau, Editor(s)

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