Name
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. 2008 SPIE and IS&T. [DOI: 10.1117/1.2957605] |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1117/1.2957605 | JOURNAL OF ELECTRONIC IMAGING |
Keywords | Field | DocType |
matrices,composites | Voxel,Computer vision,Thermal,Carbon composites,Curvature,Homogeneous,Computer science,Matrix (mathematics),Segmentation,Cylinder,Artificial intelligence | Journal |
Volume | Issue | ISSN |
17 | 3 | 1017-9909 |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christianne Mulat | 1 | 2 | 0.77 |
| Marc Donias | 2 | 45 | 7.92 |
| Pierre Baylou | 3 | 139 | 21.74 |
| Gérard L. Vignoles | 4 | 0 | 0.68 |
| Christian Germain | 5 | 113 | 18.95 |