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Increasing the discrimination power of the co-occurrence matrix-based features
Department of Applied Electronics, Kaunas University of Technology, Lithuania.
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.
2007 (English)In: Pattern Recognition, ISSN 0031-3203, E-ISSN 1873-5142, Vol. 40, no 9, p. 2367-2372Article in journal (Refereed) Published
Abstract [en]

This paper is concerned with an approach to exploiting information available from the co-occurrence matrices computed for different distance parameter values. A polynomial of degree n is fitted to each of 14 Haralick's coefficients computed from the average co-occurrence matrices evaluated for several distance parameter values. Parameters of the polynomials constitute a set of new features. The experimental investigations performed substantiated the usefulness of the approach.

Place, publisher, year, edition, pages
Oxford: Pergamon Press, 2007. Vol. 40, no 9, p. 2367-2372
Keywords [en]
Co-occurrence matrix, Image texture, Support vector machine, Computational methods, Parameter estimation, Polynomials, Set theory
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:hh:diva-1322DOI: 10.1016/j.patcog.2006.12.004ISI: 000246932200001Scopus ID: 2-s2.0-34247582309Local ID: 2082/1701OAI: oai:DiVA.org:hh-1322DiVA, id: diva2:238540
Available from: 2008-04-16 Created: 2008-04-16 Last updated: 2018-01-13Bibliographically approved

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Verikas, Antanas

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Citation style
  • apa
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  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
More languages
Output format
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  • asciidoc
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