Machine Vision Systems for Processing Hardwood Lumber and Logs

Machine vision and automated processing systems are under development at Virginia Tech University with support and cooperation from the USDA Forest Service. Our goals are to help U.S. hardwood producers automate, reduce costs, increase product volume and value recovery, and market higher value, more accurately graded and described products. Any vision system is composed of two bread tasks: image scanning and image interpretation. A rough lumber vision system recognizes board defects, clear wood, and board outlines, and labels these areas. Two available computer programs can use this defect information. The first program grades the board by National Hardwood Lumber Association grading rules. The second program simulates the processing of the board into standard or specific cuttings or part sizes by two different cutup methods. One goal of the vision system is to analyze images of rough lumber in a species-independent man-