Axis detection of cylindrical objects in three-dimensional images

Christianne Mulat; Marc Donias; Pierre Baylou; Gerard Vignoles; Christian Germain

doi:10.1117/1.2957605

Abstract

We introduce an algorithm dedicated to the detection of the axes of cylindrical objects in a 3D block. The proposed algorithm performs 3D axis detection without prior segmentation of the block. This approach is specifically appropriate when the gray levels of the cylindrical objects are not homogeneous and are 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 detects 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 performances. We detail the various steps of the algorithm and then present some results, obtained with both synthetic blocks and real data acquired by synchrotron X-ray micro-tomography on carbon-fiber-reinforced carbon composites.

Citation Download Citation

Christianne Mulat, Marc Donias, Pierre Baylou, Gerard Vignoles, Christian Germain, "Axis detection of cylindrical objects in three-dimensional images," Journal of Electronic Imaging 17(3), 031108 (1 July 2008). https://doi.org/10.1117/1.2957605 . Submission:

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