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Proceedings Paper

Strategy for grading natural materials using a two-step classification procedure
Author(s): Bjarne Kjaer Ersboll; Knut Conradsen
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Paper Abstract

Quality grading of natural materials such as fur, wood and cork has traditionally been done manually. Since the grading by humans is done by assessing the visual quality of the material it has been tempting to try to automate the process using some kind of image analysis. Much research has been devoted to solving this problem. Grading rules for natural materials usually consist of a description of which types of defects are allowed for each grade and how severe they may be. The complexity of these grading rules and the variability of natural materials taken into account makes expert system or artificial intelligence approaches infeasible. This paper proposes a method for automatic grating of natural materials using statistically based classification techniques. The method involves two classification steps: in the first step a pixel wise classification of defects is performed based upon a number of features generated from the original image; the second step utilizes the relative distribution of defects to perform a final grading assessment. The method is illustrated using the grading of beech wood slabs as an example.

Paper Details

Date Published: 28 May 1993
PDF: 12 pages
Proc. SPIE 1821, Industrial Applications of Optical Inspection, Metrology, and Sensing, (28 May 1993); doi: 10.1117/12.145549
Show Author Affiliations
Bjarne Kjaer Ersboll, Technical Univ. of Denmark (Denmark)
Knut Conradsen, Technical Univ. of Denmark (Denmark)

Published in SPIE Proceedings Vol. 1821:
Industrial Applications of Optical Inspection, Metrology, and Sensing
Gordon M. Brown; Kevin G. Harding; H. Philip Stahl, Editor(s)

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