---
_id: '10897'
abstract:
- lang: eng
  text: 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.
acknowledgement: This research is partially supported by the European Science Foundation
  (ESF) under the Research Network Programme, the European Union under the Toposys
  Project FP7-ICT-318493-STREP, the Russian Government under the Mega Project 11.G34.31.0053.
article_processing_charge: No
author:
- first_name: Herbert
  full_name: Edelsbrunner, Herbert
  id: 3FB178DA-F248-11E8-B48F-1D18A9856A87
  last_name: Edelsbrunner
  orcid: 0000-0002-9823-6833
citation:
  ama: 'Edelsbrunner H. Persistent homology in image processing. In: <i>Graph-Based
    Representations in Pattern Recognition</i>. Vol 7877. LNCS. Berlin, Heidelberg:
    Springer Nature; 2013:182-183. doi:<a href="https://doi.org/10.1007/978-3-642-38221-5_19">10.1007/978-3-642-38221-5_19</a>'
  apa: 'Edelsbrunner, H. (2013). Persistent homology in image processing. In <i>Graph-Based
    Representations in Pattern Recognition</i> (Vol. 7877, pp. 182–183). Berlin, Heidelberg:
    Springer Nature. <a href="https://doi.org/10.1007/978-3-642-38221-5_19">https://doi.org/10.1007/978-3-642-38221-5_19</a>'
  chicago: 'Edelsbrunner, Herbert. “Persistent Homology in Image Processing.” In <i>Graph-Based
    Representations in Pattern Recognition</i>, 7877:182–83. LNCS. Berlin, Heidelberg:
    Springer Nature, 2013. <a href="https://doi.org/10.1007/978-3-642-38221-5_19">https://doi.org/10.1007/978-3-642-38221-5_19</a>.'
  ieee: H. Edelsbrunner, “Persistent homology in image processing,” in <i>Graph-Based
    Representations in Pattern Recognition</i>, Vienna, Austria, 2013, vol. 7877,
    pp. 182–183.
  ista: 'Edelsbrunner H. 2013. Persistent homology in image processing. Graph-Based
    Representations in Pattern Recognition. GbRPR: Graph-based Representations in
    Pattern RecognitionLNCS vol. 7877, 182–183.'
  mla: Edelsbrunner, Herbert. “Persistent Homology in Image Processing.” <i>Graph-Based
    Representations in Pattern Recognition</i>, vol. 7877, Springer Nature, 2013,
    pp. 182–83, doi:<a href="https://doi.org/10.1007/978-3-642-38221-5_19">10.1007/978-3-642-38221-5_19</a>.
  short: H. Edelsbrunner, in:, Graph-Based Representations in Pattern Recognition,
    Springer Nature, Berlin, Heidelberg, 2013, pp. 182–183.
conference:
  end_date: 2013-05-17
  location: Vienna, Austria
  name: 'GbRPR: Graph-based Representations in Pattern Recognition'
  start_date: 2013-05-15
date_created: 2022-03-21T07:30:33Z
date_published: 2013-06-01T00:00:00Z
date_updated: 2023-09-05T15:10:20Z
day: '01'
department:
- _id: HeEd
doi: 10.1007/978-3-642-38221-5_19
ec_funded: 1
intvolume: '      7877'
language:
- iso: eng
month: '06'
oa_version: None
page: 182-183
place: Berlin, Heidelberg
project:
- _id: 255D761E-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '318493'
  name: Topological Complex Systems
publication: Graph-Based Representations in Pattern Recognition
publication_identifier:
  eisbn:
  - '9783642382215'
  eissn:
  - 1611-3349
  isbn:
  - '9783642382208'
  issn:
  - 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
series_title: LNCS
status: public
title: Persistent homology in image processing
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 7877
year: '2013'
...