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3 October 1995 Syntactic recognition of defects on wooden boards
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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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wolfgang Poelzleitner "Syntactic recognition of defects on wooden boards", Proc. SPIE 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling, (3 October 1995);


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