Paper
1 March 2005 A multisensor system for texture-based high-speed hardwood lumber inspection
Alfred Rinnhofer, Gerhard Jakob, Edwin Deutschl, Wanda Benesova, Jean-Philippe Andreu, Giuseppe Parziale, Albert Niel
Author Affiliations +
Proceedings Volume 5672, Image Processing: Algorithms and Systems IV; (2005) https://doi.org/10.1117/12.588199
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
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.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alfred Rinnhofer, Gerhard Jakob, Edwin Deutschl, Wanda Benesova, Jean-Philippe Andreu, Giuseppe Parziale, and Albert Niel "A multisensor system for texture-based high-speed hardwood lumber inspection", Proc. SPIE 5672, Image Processing: Algorithms and Systems IV, (1 March 2005); https://doi.org/10.1117/12.588199
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Cited by 3 scholarly publications.
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KEYWORDS
Image segmentation

3D metrology

Cameras

Inspection

Image classification

3D image processing

Imaging systems

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