Two-parameter persistence for images via distance transform

CS Hu, A Lawson, YM Chung… - Proceedings of the …, 2021 - openaccess.thecvf.com
CS Hu, A Lawson, YM Chung, K Keegan
Proceedings of the IEEE/CVF International Conference on …, 2021openaccess.thecvf.com
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 …
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.
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