Publicación:
IDENTIFICATION OF KNOTTY CORE IN PINUS RADIATA LOGS FROM COMPUTED TOMOGRAPHY IMAGES USING ARTIFICIAL NEURAL NETWORK

dc.creatorGERSON TEMAN ROJAS ESPINOZA
dc.date2010
dc.date.accessioned2025-01-10T15:47:23Z
dc.date.available2025-01-10T15:47:23Z
dc.date.issued2010
dc.description.abstractTHE FEASIBILITY OF IDENTIFYING KNOTTY CORE IN IMAGES OF X-RAY COMPUTED TOMOGRAPHY (CT) OF PRUNED RADIATA PINE LOGS (PINUS RADIATA D. DON), WAS EVALUATED USING A SUPERVISED CLASSIFICATION METHOD BASED ON ARTIFICIAL NEURAL NETWORKS (ANN). THE CLASSIFICATION PROCESS ALSO CONSIDERS THE IDENTIFICATION OF THE CLEAR WOOD AND KNOTS. THIRTY PRUNED RADIATA PINE LOGS WERE SCANNED IN A MULTI-SLICE SCANNER MEDICAL X-RAY, WHERE THE RESULTING CT IMAGES WERE OBTAINED EVERY 5 MM. A TOTAL OF 270 CT IMAGES WERE CLASSIFIED USING THE ANN, AND THE RESULTING THEMATIC MAPS WERE FILTERED WITH A MEDIAN FILTER OF 7 X 7. THE ACCURACY OF THE CLASSIFICATION PROCESS OF THE CT IMAGES WAS OBTAINED FROM A CONFUSION MATRIX AND KAPPA STATISTICS. THE RESULTS INDICATED THAT THE KNOTTY CORE CAN BE IDENTIFIED AND SEPARATED WITH AN ACCURACY OF 92.7%, WHILE FOR THE OVERALL ACCURACY WAS OBTAINED A VALUE OF 85.0%. AFTER FILTERING THEMATIC MAPS, THE PRECISION VALUES INCREASED TO 96.3% AND 92.3% FOR THE DEFECTIVE CORE AND OVERALL ACCURACY, RESPECTIVELY. KAPPA VALUES WERE 0.607 AND 0.764 FOR THEMATIC MAPS AND THEMATIC MAPS FILTERED, RESPECTIVELY. THESE VALUES INDICATE THAT THERE IS A STRONG DEGREE OF AGREEMENT BETWEEN REFERENCE DATA AND CLASSIFICATION PROCESS. THE RESULTS SUGGEST THAT IT IS FEASIBLE TO APPLY ARTIFICIAL NEURAL NETWORKS AS CLASSIFICATION PROCEDURE TO IDENTIFY THE KNOTTY CORE IN CT IMAGES OF PRUNED RADIATA PINE LOGS.
dc.formatapplication/pdf
dc.identifier.doi10.4067/S0718-221X2010000300007
dc.identifier.issn0717-3644
dc.identifier.issn0718-221X
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/13659
dc.languagespa
dc.publisherMADERAS: CIENCIA Y TECNOLOGIA
dc.relation.uri10.4067/S0718-221X2010000300007
dc.rightsPUBLICADA
dc.subjectradiata pine
dc.subjectKnotty core
dc.subjectconfusion matrix
dc.subjectcomputed tomography
dc.subjectartificial neural networks
dc.titleIDENTIFICATION OF KNOTTY CORE IN PINUS RADIATA LOGS FROM COMPUTED TOMOGRAPHY IMAGES USING ARTIFICIAL NEURAL NETWORK
dc.typeARTÍCULO
dspace.entity.typePublication
ubb.EstadoPUBLICADA
ubb.Otra ReparticionESCUELA INGENIERIA CIVIL EN INDUSTRIAS DE LA MADERA
ubb.SedeCONCEPCIÓN
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