Evaluation of an automated hardwood lumber grading system

  • Author(s): Kline, D. Earl; Araman, Philip A.; Surak, Chris
  • Date: 2001
  • Station ID: Miscellaneous Publication-SRS-


Over the last 10 years, scientists at the Thomas M. Brooks Forest Products Center, the Bradley Department of Electrical Engineering, and the USDA Forest Service have been working on lumber scanning systems that can accurately locate and identify defects in hardwood lumber. Current R&D efforts are targeted toward developing automated lumber grading technologies. The objective of this work is to evaluate hardwood lumber grading accuracy based on current state-of-the-art multiple sensor scanning technology that uses laser profile detectors, color cameras, and an x-ray scanner. 89 red oak boards were scanned and graded using Virginia Tech’s scanning system. A certified National Hardwood Lumber Association (NHLA) employed lumber inspector then graded the lumber. The boards were also manually digitized and mapped for defects.

The automated lumber grading system was found to be 31 percent more accurate than the company line graders. Further, the automated lumber grading system estimated lumber value to within less than 5 percent of the NHLA certified value whereas the line grader overestimated the lumber value by close to 20 percent. Most automated lumber grading discrepancies resulted from board geometry related issues (e.g. board crook, surface measure rounding, calculation of cutting units, etc.). Concerning the multiple sensor scanning system defect recognition improvements should focus on better methods to differentiate surface discoloration from critical grading defects. This study is helping to guide the development of future scanning hardware and image processing software to more accurately identify lumber grading features.

  • Citation: Kline, D. Earl; Araman, Philip A.; Surak, Chris 2001. Evaluation of an automated hardwood lumber grading system. Proceedings, ScanTech 2001, The Ninth International Conference on Scanning Technology and Process Optimization for the Wood Industry. 141-151.

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