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Proceedings Paper

A multisensor system for texture-based high-speed hardwood lumber inspection
Author(s): Alfred Rinnhofer; Gerhard Jakob; Edwin Deutschl; Wanda Benesova; Jean-Philippe Andreu; Giuseppe Parziale; Albert Niel
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Paper Abstract

A novel solution for automatic hardwood inspection is presented. A sophisticated multi sensor system is required for reliable results. Our system works on a data stream of more than 50 MByte/Sec in input and up to 100 MByte/Sec inside the processing queue. The algorithm is divided into multiple steps. Along a fixed grid the images are decomposed into small squares. 55 texture- and color features are computed for each square. A Maximum Likelihood classifier assigns each square to one out of 12 defect classes with a recognition rate better than 97%. Depending on the defect type a dedicated threshold operation is performed for segmentation. Threshold levels and the selection of the input channel (RGB + filtered images) is the result of the former classification step. A fast algorithm computes bounding rectangles from blobs. Defect type dependent rules are used to combine rectangles. Two additional fast high resolution 3D measurement systems add board shape and 3D defect information. All defect rectangles are passing an additional plausibility check in the last data fusion process before they are delivered to the optimization computer. To guarantee a short response time, image acquisition and image processing are performed in parallel on parallel computing hardware.

Paper Details

Date Published: 1 March 2005
PDF: 10 pages
Proc. SPIE 5672, Image Processing: Algorithms and Systems IV, (1 March 2005); doi: 10.1117/12.588199
Show Author Affiliations
Alfred Rinnhofer, Joanneum Research (Austria)
Gerhard Jakob, Joanneum Research (Austria)
Edwin Deutschl, Joanneum Research (Austria)
Wanda Benesova, Joanneum Research (Austria)
Jean-Philippe Andreu, Joanneum Research (Austria)
Giuseppe Parziale, Joanneum Research (Austria)
Albert Niel, Joanneum Research (Austria)

Published in SPIE Proceedings Vol. 5672:
Image Processing: Algorithms and Systems IV
Edward R. Dougherty; Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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