--- res: bibo_abstract: - Taking images is an efficient way to collect data about the physical world. It can be done fast and in exquisite detail. By definition, image processing is the field that concerns itself with the computation aimed at harnessing the information contained in images [10]. This talk is concerned with topological information. Our main thesis is that persistent homology [5] is a useful method to quantify and summarize topological information, building a bridge that connects algebraic topology with applications. We provide supporting evidence for this thesis by touching upon four technical developments in the overlap between persistent homology and image processing.@eng bibo_authorlist: - foaf_Person: foaf_givenName: Herbert foaf_name: Edelsbrunner, Herbert foaf_surname: Edelsbrunner foaf_workInfoHomepage: http://www.librecat.org/personId=3FB178DA-F248-11E8-B48F-1D18A9856A87 orcid: 0000-0002-9823-6833 bibo_doi: 10.1007/978-3-642-38221-5_19 bibo_volume: 7877 dct_date: 2013^xs_gYear dct_isPartOf: - http://id.crossref.org/issn/0302-9743 - http://id.crossref.org/issn/1611-3349 - http://id.crossref.org/issn/9783642382208 dct_language: eng dct_publisher: Springer Nature@ dct_title: Persistent homology in image processing@ ...