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Evaluating the Impact of Color on Texture Recognition
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
Universitat Autonoma de Barcelona, Spain .
Universitat Autonoma de Barcelona, Spain .
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-6096-3648
2013 (English)In: Computer Analysis of Images and Patterns: 15th International Conference, CAIP 2013, York, UK, August 27-29, 2013, Proceedings, Part I / [ed] Richard Wilson, Edwin Hancock, Adrian Bors, William Smith, Springer Berlin/Heidelberg, 2013, 154-162 p.Conference paper, Published paper (Refereed)
Abstract [en]

State-of-the-art texture descriptors typically operate on grey scale images while ignoring color information. A common way to obtain a joint color-texture representation is to combine the two visual cues at the pixel level. However, such an approach provides sub-optimal results for texture categorisation task.

In this paper we investigate how to optimally exploit color information for texture recognition. We evaluate a variety of color descriptors, popular in image classification, for texture categorisation. In addition we analyze different fusion approaches to combine color and texture cues. Experiments are conducted on the challenging scenes and 10 class texture datasets. Our experiments clearly suggest that in all cases color names provide the best performance. Late fusion is the best strategy to combine color and texture. By selecting the best color descriptor with optimal fusion strategy provides a gain of 5% to 8% compared to texture alone on scenes and texture datasets.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2013. 154-162 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 8047
Keyword [en]
Color, texture, image representation
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-105460DOI: 10.1007/978-3-642-40261-6_18ISI: 000345516500018ISBN: 978-3-642-40260-9 (print)ISBN: 978-3-642-40261-6 (print)OAI: oai:DiVA.org:liu-105460DiVA: diva2:707460
Conference
15th International Conference on Computer Analysis of Images and Patterns (CAIP 2013), York, UK, 27-29 August 2013
Projects
CUAS , ELLIT
Available from: 2014-03-24 Created: 2014-03-24 Last updated: 2016-05-04Bibliographically approved

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Khan, Fahad ShahbazFelsberg, Michael

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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  • Other style
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Language
  • de-DE
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  • sv-SE
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Output format
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