Objective In order to realize the three-dimensional reconstruction of targeted defects and provide technical support for the application of CT technology in wood materials, the defect types, spatial distribution and morphological characteristics of Pinus massoniana log were interpreted based on computerized tomography (CT) images.

Method Reasonable parameters were set to quickly complete the scanning of P. massoniana logs. For CT image of the defects in P. massoniana log, the curvature anisotropic diffusion filtering was used to reduce noise. The threshold segmentation was applied to realize the segmentation of crack and insect hole by selecting reasonable thresholds, and the parametric deformation modeling algorithm was used to realize the segmentation of knots. Using Mimics software, the three-dimensional model of crack and insect hole was established by 3D area growth method. Based on MITK Workbench software, the 3D model of knots was established using the moving cube algorithm in 3D visualization surface rendering of VTK.

Result The threshold segmentation method and parameter deformation modeling method can quickly and accurately identify the internal defects of logs and extract the defect feature information, which had high identification efficiency and accuracy. The relative error was small, fluctuating within the range of 3.63%−10.36%. The three-dimensional reconstruction of internal cracks, insect holes and knot was realized by three-dimensional region growth method and the moving cube algorithm, which can quickly obtain the spatial distribution, structural characteristics and quantify the feature information of defects.

Conclusion An image segmentation and three-dimensional visualization method suitable for different defects is proposed, the spatial distribution location and characteristic parameters of the defects in P. massoniana logs are obtained, and the accuracy of defect detection is high. The research results can provide technical support for wood protection and utilization improvement.