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Updated: Aug 1, 2025

Extracting Metrics for Three-dimensional Root Systems: Volume and Surface Analysis from In-soil X-ray Computed Tomography Data
Published on: April 26, 2016
RGB-D microtopography: A comprehensive dataset for surface analysis and characterization techniques
Stefan Siemens1, Markus Kästner1, Eduard Reithmeier1
1Institute of Measurement and Automatic Control, Leibniz University Hannover, An der Universität 1, 30823 Garbsen, Germany.
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.

