Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Fuzzy Granulation Approach to Face Recognition
University of Social Sciences, POL.
Czestochowa University of Technology, POL.
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-9920-7946
2021 (English)In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) / [ed] Rutkowski L., Scherer R., Korytkowski M., Pedrycz W., Tadeusiewicz R., Zurada J.M., Springer Science and Business Media Deutschland GmbH , 2021, Vol. 12855, p. 495-510Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, a new approach to face description is proposed. The linguistic description of human faces in digital pictures is generated within a framework of fuzzy granulation. Fuzzy relations and fuzzy relational rules are applied in order to create the image description. By use of type-2 fuzzy sets, fuzzy relations, and fuzzy IF-THEN rules, an image recognition system can infer and explain its decision. Such a system can retrieve an image, recognize, and classify – especially a human face – based on the linguistic description. © 2021, Springer Nature Switzerland AG.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH , 2021. Vol. 12855, p. 495-510
Series
Lecture Notes in Computer Science, ISSN 03029743, E-ISSN 16113349
Keywords [en]
Explainable AI, Face recognition, Fuzzy granulation, Fuzzy relations, Fuzzy rules, Linguistic description, Type-2 fuzzy sets, Fuzzy inference, Granulation, Intelligent systems, Linguistics, Digital picture, Face descriptions, Human faces, Image descriptions, Linguistic descriptions, New approaches, Type-2 fuzzy set
National Category
Computer Sciences Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:bth-22305DOI: 10.1007/978-3-030-87897-9_44ISI: 000811814800043Scopus ID: 2-s2.0-85117706489ISBN: 9783030878962 (print)OAI: oai:DiVA.org:bth-22305DiVA, id: diva2:1609301
Conference
20th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2021,Virtual, Online, 21 June through 23 June
Available from: 2021-11-08 Created: 2021-11-08 Last updated: 2022-08-08Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Rakus-Andersson, Elisabeth

Search in DiVA

By author/editor
Rakus-Andersson, Elisabeth
By organisation
Department of Mathematics and Natural Sciences
Computer SciencesComputer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 51 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf