Surface topography refers to the geometric micro-structure of a surface and defines its tactile characteristics (typically in the sub-millimeter range). High-resolution 3D scanning techniques developed recently enable the 3D reconstruction of surfaces including their surface topography. In his paper, we present an efficient image-space technique for the extraction of surface topography from high-resolution 3D reconstructions. Additionally, we filter noise and enhance topographic attributes to obtain an improved representation for subsequent topography classification. Comprehensive experiments show that the our representation captures well topographic attributes and significantly improves classification performance compared to alternative 2D and 3D representations.
@article{arxiv.1504.08308,
title = {Efficient Image-Space Extraction and Representation of 3D Surface Topography},
author = {Matthias Zeppelzauer and Markus Seidl},
journal= {arXiv preprint arXiv:1504.08308},
year = {2015}
}
Comments
Initial version of the paper accepted at the IEEE ICIP Conference 2015