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arXiv 2005.126922020-05cs.CVmath.AT

Cubical Ripser: Software for computing persistent homology of image and volume data

Institute of Mathematics for Industry, Kyushu University（九州大学产业数学研究所）；School of Interdisciplinary Mathematical Sciences, Meiji University（明治大学跨学科数理科学学院）

Shizuo Kaji, Takeki Sudo, Kazushi Ahara

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We introduce Cubical Ripser for computing persistent homology of image and volume data (more precisely, weighted cubical complexes). To our best knowledge, Cubical Ripser is currently the fastest and the most memory-efficient program for computing persistent homology of weighted cubical complexes. We demonstrate our software with an example of image analysis in which persistent homology and convolutional neural networks are successfully combined. Our open-source implementation is available online.

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