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A modular approach to detection and identification of defects in rough lumber

Informally Refereed

Abstract

This paper describes a prototype scanning system that can automatically identify several important defects on rough hardwood lumber. The scanning system utilizes 3 laser sources and an embedded-processor camera to capture and analyze profile and gray-scale images. The modular approach combines the detection of wane (the curved sides of a board, possibly containing residual bark) with classification of defects. For identifying clear(unblemished) wood, a multilayer perception network is used; and for other defects, statistically trained radial-basis-function networks are implemented, followed by a competitive decision scheme. The system is among the first to scan and evaluate lumber in its rough (unplaned) state.

Citation

Lee, Sang Mook; Abbott, A. Lynn; Schmoldt, Daniel L. 2001. A modular approach to detection and identification of defects in rough lumber. Review of Progress in Nondestructive Evaluation. 20: 1950-1957.
https://www.fs.usda.gov/research/treesearch/2378