RGB-D microtopography: A comprehensive dataset for surface analysis and characterization techniques

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OriginalspracheEnglisch
Aufsatznummer109094
FachzeitschriftData in Brief
Jahrgang48
Frühes Online-Datum28 März 2023
PublikationsstatusVeröffentlicht - Juni 2023

Abstract

The dataset presented contains microtopographies of various materials and processing methods. These microtopographies were measured using a Confocal Laser Scanning Microscope, which provides RGB-D data. This means the dataset comprises accurate height maps for each measurement and microscopic RGB images. The height maps can be used to quantify and characterize small-scale surface features such as pits and grooves, surface roughness, texture direction, and surface anisotropy. These features can significantly impact a material's properties and behavior, making them essential in many fields, such as biomaterials and tribology. Additionally, the dataset contains metadata about the specimens and the measurement conditions, such as material, surface processing method, roughness, and optical magnification. Therefore, this dataset provides an opportunity to develop and test surface classification and characterization algorithms.

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RGB-D microtopography: A comprehensive dataset for surface analysis and characterization techniques. / Siemens, Stefan; Kästner, Markus; Reithmeier, Eduard.
in: Data in Brief, Jahrgang 48, 109094, 06.2023.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Siemens S, Kästner M, Reithmeier E. RGB-D microtopography: A comprehensive dataset for surface analysis and characterization techniques. Data in Brief. 2023 Jun;48:109094. Epub 2023 Mär 28. doi: 10.1016/j.dib.2023.109094
Siemens, Stefan ; Kästner, Markus ; Reithmeier, Eduard. / RGB-D microtopography : A comprehensive dataset for surface analysis and characterization techniques. in: Data in Brief. 2023 ; Jahrgang 48.
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abstract = "The dataset presented contains microtopographies of various materials and processing methods. These microtopographies were measured using a Confocal Laser Scanning Microscope, which provides RGB-D data. This means the dataset comprises accurate height maps for each measurement and microscopic RGB images. The height maps can be used to quantify and characterize small-scale surface features such as pits and grooves, surface roughness, texture direction, and surface anisotropy. These features can significantly impact a material's properties and behavior, making them essential in many fields, such as biomaterials and tribology. Additionally, the dataset contains metadata about the specimens and the measurement conditions, such as material, surface processing method, roughness, and optical magnification. Therefore, this dataset provides an opportunity to develop and test surface classification and characterization algorithms.",
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T2 - A comprehensive dataset for surface analysis and characterization techniques

AU - Siemens, Stefan

AU - Kästner, Markus

AU - Reithmeier, Eduard

N1 - Funding Information: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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AB - The dataset presented contains microtopographies of various materials and processing methods. These microtopographies were measured using a Confocal Laser Scanning Microscope, which provides RGB-D data. This means the dataset comprises accurate height maps for each measurement and microscopic RGB images. The height maps can be used to quantify and characterize small-scale surface features such as pits and grooves, surface roughness, texture direction, and surface anisotropy. These features can significantly impact a material's properties and behavior, making them essential in many fields, such as biomaterials and tribology. Additionally, the dataset contains metadata about the specimens and the measurement conditions, such as material, surface processing method, roughness, and optical magnification. Therefore, this dataset provides an opportunity to develop and test surface classification and characterization algorithms.

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