Axis detection of cylindrical objects in 3-D images

Overview & Synopsis

This paper introduces an algorithm dedicated to the detection of the axes of cylindrical objects in a 3-D block. The proposed algorithm performs the 3-D axis detection without prior segmentation of the block. This approach is specifically appropriate when the grey levels of the cylindrical objects are not homogeneous and thus difficult to distinguish from the background. The method relies on gradient and curvature estimation and operates in two main steps. The first one selects candidate voxels for the axes and the second one refines the determination of the axis of each cylindrical object. Applied to fiber reinforced composite materials, this algorithm allows detecting the axes of fibers in order to obtain the geometrical characteristics of the reinforcement. Knowing the reinforcement characteristics is an important issue in the quality control of the material but also in the prediction of the thermal and mechanical performance. In this paper, the various steps of the algorithm are detailed. Then, some results are presented, obtained with both synthetic blocks and real data acquired by synchrotron X-ray micro tomography on carbon-fiber reinforced carbon composites.