3D registration of depth data of porous surface coatings based on 3D phase correlation and the trimmed ICP algorithm

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Loftfield, N.; Kästner, M.; Reithmeier, E.: 3D registration of depth data of porous surface coatings based on 3D phase correlation and the trimmed ICP algorithm. In: Proceedings of SPIE - The International Society for Optical Engineering 10333 (2017), 1033310. DOI: https://doi.org/10.1117/12.2269781

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Sum total of downloads: 141

A critical factor of endoprostheses is the quality of the tribological pairing. The objective of this research project is to manufacture stochastically porous aluminum oxide surface coatings with high wear resistance and an active friction minimization. There are many experimental and computational techniques from mercury porosimetry to imaging methods for studying porous materials, however, the characterization of disordered pore networks is still a great challenge. To meet this challenge it is striven to gain a three dimensional high resolution reconstruction of the surface. In this work, the reconstruction is approached by repeatedly milling down the surface by a fixed decrement while measuring each layer using a confocal laser scanning microscope (CLSM). The so acquired depth data of the successive layers is then registered pairwise. Within this work a direct registration approach is deployed and implemented in two steps, a coarse and a fine alignment. The coarse alignment of the depth data is limited to a translational shift which occurs in horizontal direction due to placing the sample in turns under the CLSM and the milling machine and in vertical direction due to the milling process itself. The shift is determined by an approach utilizing 3D phase correlation. The fine alignment is implemented by the Trimmed Iterative Closest Point algorithm, matching the most likely common pixels roughly specified by an estimated overlap rate. With the presented two-step approach a proper 3D registration of the successive depth data of the layer is obtained. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
License of this version: Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. Dieser Beitrag ist aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
Document Type: article
Publishing status: publishedVersion
Issue Date: 2017
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of Germany Germany 95 67.38%
2 image of flag of United States United States 13 9.22%
3 image of flag of China China 9 6.38%
4 image of flag of Netherlands Netherlands 4 2.84%
5 image of flag of United Kingdom United Kingdom 3 2.13%
6 image of flag of France France 3 2.13%
7 image of flag of No geo information available No geo information available 2 1.42%
8 image of flag of Hungary Hungary 2 1.42%
9 image of flag of Czech Republic Czech Republic 2 1.42%
10 image of flag of Vietnam Vietnam 1 0.71%
    other countries 7 4.96%

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