Automated Planning and Optimization of Lumber Production Using Machine Vision and Computed Tomography

被引:30
作者
Bhandarkar, Suchendra M. [1 ]
Luo, Xingzhi [1 ]
Daniels, Richard F. [2 ]
Tollner, E. William [3 ]
机构
[1] Univ Georgia, Dept Comp Sci, Athens, GA 30602 USA
[2] Univ Georgia, Warnell Sch Forest Resources, Athens, GA 30602 USA
[3] Univ Georgia, Dept Biol & Agr Engn, Athens, GA 30602 USA
关键词
Automated lumber grading; automated lumber production; computed tomography (CT); lumber production optimization; nondestructive evaluation;
D O I
10.1109/TASE.2008.925254
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An automated system for planning and optimization of lumber production using Machine Vision and Computed Tomography (CT) is proposed. Cross-sectional CT images of hardwood logs are analyzed using machine vision algorithms. Internal defects in the hardwood logs pockets are identified and localized. A virtual in silico 3-D reconstruction of the,hardwood log and its internal defects is generated using Kalman filter-based tracking algorithms. Various sawing operations are simulated on the virtual 3-D reconstruction of the log and the resulting virtual lumber products automatically graded using rules stipulated by the National Hardwood Lumber Association (NHLA). Knowledge of the internal log defects is suitably exploited to formulate sawing strategies that optimize the value yield recovery of the resulting lumber products. A prototype implementation shows significant gains in value yield recovery when compared with lumber processing strategies that use only the information derived from the external log structure.
引用
收藏
页码:677 / 695
页数:19
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