Wane detection on rough lumber using surface approximation

Abstract

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.

Citation

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.