hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Integrating global and local analysis of color, texture and geometrical information for categorizing laryngeal images
Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0003-2185-8973
Department of Applied Electronics, Kaunas University of Technology, Lithuania.
Department of Applied Electronics, Kaunas University of Technology, Lithuania.
Department of Otolaryngology, Kaunas University of Medicine, Lithuania.
2006 (English)In: International journal of pattern recognition and artificial intelligence, ISSN 0218-0014, Vol. 20, no 8, p. 1187-1205Article in journal (Refereed) Published
Abstract [en]

An approach to integrating the global and local kernel-based automated analysis of vocal fold images aiming to categorize laryngeal diseases is presented in this paper. The problem is treated as an image analysis and recognition task. A committee of support vector machines is employed for performing the categorization of vocal fold images into healthy, diffuse and nodular classes. Analysis of image color distribution, Gabor filtering, cooccurrence matrices, analysis of color edges, image segmentation into homogeneous regions from the image color, texture and geometry view point, analysis of the soft membership of the regions in the decision classes, the kernel principal components based feature extraction are the techniques employed for the global and local analysis of laryngeal images. Bearing in mind the high similarity of the decision classes, the correct classification rate of over 94% obtained when testing the system on 785 vocal fold images is rather encouraging.

Place, publisher, year, edition, pages
Singapore: World Scientific, 2006. Vol. 20, no 8, p. 1187-1205
Keywords [en]
Laryngeal image, Color, Texture, Gabor filtering, Cooccurrence matrix, Support vector machine
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hh:diva-3535DOI: 10.1142/S0218001406005228ISI: 000243988600004Scopus ID: 2-s2.0-33845728186OAI: oai:DiVA.org:hh-3535DiVA, id: diva2:286852
Available from: 2010-01-15 Created: 2009-12-01 Last updated: 2018-01-12Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Verikas, Antanas

Search in DiVA

By author/editor
Verikas, Antanas
By organisation
Halmstad Embedded and Intelligent Systems Research (EIS)
In the same journal
International journal of pattern recognition and artificial intelligence
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 144 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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