Abstract:
We propose novel thinning conditions for grayscale 3D images that do not rely on image thresholding or segmentation. The resulting grayscale skeletonization routine extracts a topologically-consistent skeleton of
curve-like features at all scales and intensities of the image. Our thinning conditions yield rich structural data that can be used to identify and delete low-contrast shape features created by blurring and noise.
Bibtex:
@ARTICLE{ag-re1sg3i-08,
title={Robust extraction of 1D skeletons from grayscale 3D images},
author={Antunez, Emilio and Guibas, Leonidas},
journal={Pattern Recognition, 2008. 19th International Conference on},
year={2008},
month={Dec.},
volume={},
number={},
pages={1-4},
doi={10.1109/ICPR.2008.4761733},
ISSN={1051-4651}, }
