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Proceedings Paper

Automated optical grading of timber
Author(s): Peter J. Sobey
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Paper Abstract

Australia grows large quantities of radiata pine for domestic consumption and a significant proportion of this is graded to an Australian Standard Appearance Grade. This paper describes automating the visual inspection of this timber in order to speed processing and improve quality control of the product. The requirement is to detect and identify the visual features on the surface of the timber after the surface has been dressed. These features include sound and encased knots of various sizes pith bark bluestain holes and wane. The image is captured using a linear array CCD camera as the board moves underneath on a conveyor belt. The first stage is to detect the areas that contain features. The image is divided into smaller local areas and first and second order statistical measures are calculated. These form the input to a neural network that has been trained to classify the local areas into clear and feature areas. The choice of measures is crucial to the ability of the neural network to perform the classification of local areas. The second stage is to determine the type of feature in the feature local areas. Various methods are employed to determine a threshold that segments the feature correctly. The size of the feature can be used to identify it uniquely. The list of features and their positions forms the input to the grading program. The grading rules defmed

Paper Details

Date Published: 1 February 1991
PDF: 12 pages
Proc. SPIE 1379, Optics in Agriculture, (1 February 1991); doi: 10.1117/12.25088
Show Author Affiliations
Peter J. Sobey, Australian National Univ. (Australia)


Published in SPIE Proceedings Vol. 1379:
Optics in Agriculture
James A. DeShazer; George E. Meyer, Editor(s)

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