Two-Parameter Persistence for Images via Distance Transform
Abstract
The distance transform of a binary image is a classic tool in computer vision and it has been widely used in the field of Topological Data Analysis (TDA) to study porous media. A common practice is to convert grayscale images to binary ones to apply the distance transform. In this work, by considering the threshold decomposition of a grayscale image, we prove that threshold decomposition and distance transform together to formulate a two-parameter filtration. This would offer the TDA community a concrete example to apply multi-parameter persistence on digital image analysis. We demonstrate our method on the firn dataset.
Cite
Text
Hu et al. "Two-Parameter Persistence for Images via Distance Transform." IEEE/CVF International Conference on Computer Vision Workshops, 2021. doi:10.1109/ICCVW54120.2021.00464Markdown
[Hu et al. "Two-Parameter Persistence for Images via Distance Transform." IEEE/CVF International Conference on Computer Vision Workshops, 2021.](https://mlanthology.org/iccvw/2021/hu2021iccvw-twoparameter/) doi:10.1109/ICCVW54120.2021.00464BibTeX
@inproceedings{hu2021iccvw-twoparameter,
title = {{Two-Parameter Persistence for Images via Distance Transform}},
author = {Hu, Chuan-Shen and Lawson, Austin and Chung, Yu-Min and Keegan, Kaitlin},
booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
year = {2021},
pages = {4159-4167},
doi = {10.1109/ICCVW54120.2021.00464},
url = {https://mlanthology.org/iccvw/2021/hu2021iccvw-twoparameter/}
}