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Proceedings Paper

Syntactic recognition of defects on wooden boards
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Paper Abstract

This paper describes a method to classify the various patterns that make up the appearance of wooden surfaces. Such surfaces are characterized by their textural appearance as well as compact convex objects like knots, holes, resin, cracks, grain lines. Many approaches to describe such surfaces have been published in the past. The list includes, but is not limited to, Hough transform methods, 2D shape recognition, fuzzy set approaches for segmentation, hierarchical pattern recognition, associative memories, and so on. In the present paper we assume that a local textural representation is computed permitting the description of the graylevel image in terms of texture elements or symbols. Using the symbolic image it is shown, how segmentation into objects can be achieved, followed by the extraction the symbolic contour as a list of symbols. Every object is described by a list of symbols to be classified using the syntactic pattern recognition. Each class of objects is described by a formal language, and parsing each string, a classification can be obtained from the grammar that causes the least amount of parsing errors. We describe details of the system, including how symbolic descriptions can be obtained, and the implementation of Earley's parser on a parallel computer architecture.

Paper Details

Date Published: 3 October 1995
PDF: 13 pages
Proc. SPIE 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling, (3 October 1995); doi: 10.1117/12.222678
Show Author Affiliations
Wolfgang Poelzleitner, Joanneum Research (Austria)


Published in SPIE Proceedings Vol. 2588:
Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling
David P. Casasent, Editor(s)

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