Wood Broken Defect Detection With 3D Laser Scanning

Wood broken defects, such as cracks, penetrating dead knots and wanes, will seriously weaken the strength of the wood and destroy the structral integrity of the wood. Therefore, these defects should be inspected and then cut during the production. Although vision-based detection methods have been proposed to detect wood defect regions, they can not detect the defects that change in depth. To solve this problem, this paper focuses on the defect detection by measuring depth difference through 3D laser data. First, the 3D laser data is preprocessed to remove the noise. Secondly, we construct a support profile by multiple mean filtering at the line-level. Next, the residual components are obtained by subtracting the support profile from the profile data and the defect is determined by comparing the residual components and the setting threshold. Finally, we perform merging and filtering operation to determine the final position of defects. The experimental results verify the effectiveness of the proposed method.