A prototype vision system for analyzing CT imagery of hardwood logs.
To fully optimize the value of material produced from a hardwood log requires information about type and location of internal defects in the log. This paper describes a prototype vision system that automatically locates and identifies certain classes of defects in hardwood logs. This system uses computer tomograph (CT) imagery. The system uses a number of processing steps. A set of basic features are defined to capture basic 3-D characteristics of wood defects. For 3-D object (defect) recognition, a set of hypothesis tests are employed that use this set of features. To further help cope with the above mentioned variability, the Dempster-Shafer theory of evidential reasoning is used to classify defect objects. Results of preliminary experiments employing two different types of hardwood logs are given.
Zhu
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D
Bradley Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA.
Conners
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RW
Schmoldt
D L
DL
Araman
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PA