Knot detection from laser point clouds for multimodal matching of wooden material

Abstract

The goal of this thesis is to establish the effectiveness of using the laser scanning for detecting knots for the task of tracking wood for the sawing process. This thesis describes the method of detecting wooden knots from point cloud images of debarked logs by analyzing the stem surface images. To convert the 3-D log surface data to the 2-D image of the surface, every cross-section of the log was fitted by a circle. Radial distances were calculated between circle and log surface points to unroll the log surface onto a 2-D coordinate space. Areas with elevated height above the approximated cylinder surface were identified as areas of the alleged location of the knots. The results were evaluated by using data obtained from the X-ray scanning of the log and it was shown that the detection results correspond well with the true knot cluster locations computed using the X-ray data. Further, the information about the knot positions can be used to match logs and sawn boards.