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作者机构:College of Computer Science and TechnologyChangzhou UniversityChangzhou 213164People’s Republic of China College of Mechanical and Electrical EngineeringNortheast Forestry UniversityHarbin 150040People’s Republic of China
出 版 物:《Journal of Forestry Research》 (林业研究(英文版))
年 卷 期:2023年第34卷第4期
页 面:1145-1152页
核心收录:
学科分类:082902[工学-木材科学与技术] 08[工学] 0829[工学-林业工程]
基 金:supported fi nancially by the China State Forestry Administration“948”projects(2015-4-52) and Hei-longjiang Natural Science Foundation(C2017005)
主 题:Timber knot inversion Distance regularized level set segmentation(DRLSE) Ellipse fi tting K-medoids cluster
摘 要:The comprehensive utilization of wood is the main goal of log cutting,but knot defects increase the diffi-culty of rationally optimizing *** to the lack of real shape data of knot defects in logs,it is diffi cult for detection methods to establish a correlation between signal and defect *** image-processing method is proposed for knot inversion based on distance regularized level set segmentation(DRLSE)and spatial vertex clustering,and with the inversion of the defects existing relative board position in the log,an inversion model of the knot defect is ***,the defect edges of the top and bottom images of the boards are extracted by DRLSE and ellipse fi tting,and the major axes of the ellipses made coplanar by angle correction;second,the coordinate points of the top and bottom ellipse edges are extracted to form a spatial straight line;third,to solve the intersection dispersion of spatial straight lines and the major axis plane,K-medoids clustering is used to locate the ***,with the vertex and the large ellipse,a 3D cone model is constructed which can be used to invert the shape of knots in the *** experiment was conducted on ten defective larch boards,and the experimental results showed that this method can accurately invert the shapes of defects in solid wood boards with the advantages of low cost and easy operation.