A Comparison of Artificial Neural Network Classifiers for Analysis of CT Images for the Inspection of Hardwood Logs

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dc.contributor.authorHe, Jingen
dc.contributor.committeechairAbbott, A. Lynnen
dc.contributor.committeememberVanLandingham, Hugh F.en
dc.contributor.committeememberSchmoldt, Daniel L.en
dc.contributor.departmentElectrical Engineeringen
dc.date.accessioned2014-03-14T20:51:13Zen
dc.date.adate1998-04-01en
dc.date.available2014-03-14T20:51:13Zen
dc.date.issued1997-09-15en
dc.date.rdate1998-04-01en
dc.date.sdate1997-09-15en
dc.description.abstractThis thesis describes an automatic CT image interpretation approach that can be used to detect hardwood defects. The goal of this research has been to develop several automatic image interpretation systems for different types of wood, with lower-level processing performed by feed forward artificial neural networks. In the course of this work, five single-species classifiers and seven multiple-species classifiers have been developed for 2-D and 3-D analysis. These classifiers were trained with back-propagation, using training samples of three species of hardwood: cherry, red oak and yellow poplar. These classifiers recognize six classes: heartwood (clear wood), sapwood, knots, bark, split s and decay. This demonstrates the feasibility of developing general classifiers that can be used with different types of hardwood logs. This will help sawmill and veneer mill operators to improve the quality of products and preserve natural resources.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-3198-94046en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-3198-94046/en
dc.identifier.urihttp://hdl.handle.net/10919/36601en
dc.publisherVirginia Techen
dc.relation.haspartpart1.pdfen
dc.relation.haspartpart2.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjecthardwooden
dc.subjectartificial neural networken
dc.subjectCT imageen
dc.titleA Comparison of Artificial Neural Network Classifiers for Analysis of CT Images for the Inspection of Hardwood Logsen
dc.typeThesisen
thesis.degree.disciplineElectrical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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