Adaptive Edge and Defect Detection as a basis for Automated Lumber Classification and Optimisation

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Abstract

One of the most demanding industrial applications for the adaptive algorithms described in the earlier chapter is the sorting of sawn lumber. Sorting is a necessary precondition for the appropriate use of sawn lumber. The sorting quality defines their possible use and is therefore of high economic importance for all areas of wood treatment and processing. A piece of wood is usually processed at a very high speed (up to 5ms−1). Therefore, a quick and effective grading of the sawn lumber is not possible without process automation. However, as a natural product, wood shows irregular, non-repeating patterns and defects. This fact requires additional efforts during visual examination and represents the greatest difficulty in wood assessment. It is due to the adaptive algorithm that an automated sorting of sawn lumber is possible satisfying the requirements of the industry. Before the corresponding algorithms are dealt with, we will give an overview of the basic terms and methods of lumber sorting.

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Louban, R. (2009). Adaptive Edge and Defect Detection as a basis for Automated Lumber Classification and Optimisation. In Springer Series in Materials Science (Vol. 123, pp. 99–128). Springer Verlag. https://doi.org/10.1007/978-3-642-00683-8_7

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