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Proceedings Paper

Real-time classification of wooden boards
Author(s): Wolfgang Poelzleitner; Gert Schwingskakl
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Paper Abstract

In this paper the design of a prototype system for real-time classification of wooden profiled boards is described. The presentation gives an overview of the algorithms and hardware developed to achieve classification in real-time at a data rate of 4Mpixel/sec. The system achieves its performance by a hierarchical processing strategy where the intensity information in the digital image is transformed into a symbolic description of small texture elements. Based on this symbolic representation a syntactic segmentation scheme is applied which produces a list of objects that are present on the board surface. The objects are described by feature vectors containing both numeric structural texture- and shape-related properties. A graph-like decision network is then used to recognize the various defects. The classification procedures were extensively tested for spruce boards on a large data set containing 500 boards taken from the production line at random. The overall rate of correct classification was 95 on this data set. The structure of these algorithms is reflected in the hardware design. We use a multiprocessor system where each processor is specialized to solve a specific task in the recognition hierarchy.

Paper Details

Date Published: 1 February 1991
PDF: 12 pages
Proc. SPIE 1384, High-Speed Inspection Architectures, Barcoding, and Character Recognition, (1 February 1991); doi: 10.1117/12.25308
Show Author Affiliations
Wolfgang Poelzleitner, Joanneum Research (Austria)
Gert Schwingskakl, Joanneum Research (Austria)


Published in SPIE Proceedings Vol. 1384:
High-Speed Inspection Architectures, Barcoding, and Character Recognition
Michael J. W. Chen, Editor(s)

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