Axis detection method for cylindrical objects

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

doi:10.1117/12.736727

29 May 2007 Axis detection method for cylindrical objects

Christianne Mulat, Marc Donias, Pierre Baylou, Gérard Vignoles, Christian Germain

Proceedings Volume 6356, Eighth International Conference on Quality Control by Artificial Vision; 63560U (2007) https://doi.org/10.1117/12.736727
Event: Eighth International Conference on Quality Control by Artificial Vision, 2007, Le Creusot, France

Abstract

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 object 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 axis 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 behavior. In this paper, the various steps of the algorithm are detailed. Then, results obtained with synthetic blocks and with blocks acquired by synchrotron X-ray microtomography on actual carbon-fiber reinforced carbon (C/C) composites are presented.

Citation Download Citation

Christianne Mulat, Marc Donias, Pierre Baylou, Gérard Vignoles, and Christian Germain "Axis detection method for cylindrical objects", Proc. SPIE 6356, Eighth International Conference on Quality Control by Artificial Vision, 63560U (29 May 2007); https://doi.org/10.1117/12.736727

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KEYWORDS

Composites

3D image processing

Detection and tracking algorithms

Image segmentation

Signal to noise ratio

X-rays

Image filtering

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