Skip to Main Content
U.S. Forest Service
Caring for the land and serving people

United States Department of Agriculture

Home > Search > Publication Information

  1. Share via EmailShare on FacebookShare on LinkedInShare on Twitter
    Dislike this pubLike this pub
    Author(s): Sang-Mook Lee; A. Lynn Abbott; Daniel L. Schmoldt
    Date: 2000
    Source: Proceedings, 4th International Conference on Image Processing and Scanning of Wood. 115-126.
    Publication Series: Miscellaneous Publication
    PDF: View PDF  (506.56 KB)


    The initial breakdown of hardwood logs into lumber produces boards with rough surfaces. These boards contain wane (missing wood due to the curved log exterior) that is removed by edge and trim cuts prior to sale. Because hardwood lumber value is determined using a combination of board size and quality, knowledge of wane position and defects is essential for selecting cuts that maximize profit. We have developed a system that uses a structured-light system to obtain profile (thickness) images of unplaned boards, in addition to gray-scale images for defect detection. The focus of this paper is to describe a new approach for detecting wane boundaries through the analysis of these profile images. The problem is difficult because bark and other debris adversely affect the laser-based imaging process, and because variations in surface reflectance also cause inaccuracies in the resulting images. The problem is compounded by the need to perform wane detection rapidly in a manufacturing environment. The method that we have developed relies on a combination of column-wise image statistics, selective smoothing, and the analysis of surface shape. Initial wane edge estimates that are obtained using the smoothed image are then refined by analysis of the original image data. Based on visual assessment, the current method appears to improve dramatically on traditional thresholding techniques.

    Publication Notes

    • You may send email to to request a hard copy of this publication.
    • (Please specify exactly which publication you are requesting and your mailing address.)
    • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.


    Lee, Sang-Mook; Abbott, A. Lynn; Schmoldt, Daniel L. 2000. Wane detection on rough lumber using surface approximation. Proceedings, 4th International Conference on Image Processing and Scanning of Wood. 115-126.

    Related Search

    XML: View XML
Show More
Show Fewer
Jump to Top of Page