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    Author(s): Philip A. Araman; Daniel L. Schmoldt; Tai-Hoon Cho; Dongping Zhu; Richard W. Conners; D. Earl Kline
    Date: 1992
    Source: AI Applications. 6(2): 13-26.
    Publication Series: Miscellaneous Publication
    PDF: Download Publication  (334 KB)


    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 broad 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 cut-up methods. One goal of the vision system is to analyze images of rough lumber in a species-independent manner. A second machine vision system deals with log scanning. This system is being developed to recognize log defects, clear wood, and log outlines and to label defect areas. This information can help sawmill operators sort logs as veneer or sawlogs, crosscut long roundwood into logs, determine how to flitch a veneer log for slicing, and determine processing for a sawlog.

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    Araman, Philip A.; Schmoldt, Daniel L.; Cho, Tai-Hoon; Zhu, Dongping; Conners, Richard W.; Kline, D. Earl. 1992. Machine Vision Systems for Processing Hardwood Lumber and Logs. AI Applications. 6(2): 13-26.

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