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Progress in Persistence for Shape Analysis (Extended Abstract)

  • Massimo FerriEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9667)

Abstract

Persistent topology mitigates the excessive freedom of topological equivalence by studying not just a topological space but a filtration of it. This makes it a very effective class of shape descriptors, with an impressive potential for applications in the image context, in particular when it comes to images of natural origin. Research in this field is lively and follows various threads. The talk will sample some recent results without any attempt to completeness.

Keywords

Betti Number Shape Descriptor Melanocytic Lesion Effective Class Massey Product 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

Work performed under the auspices of INdAM-GNSAGA.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Dip. di Matematica e ARCESUniv. di BolognaBolognaItaly

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