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Evaluating the Impa...
Evaluating the Impact of Color on Texture Recognition
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- Khan, Fahad Shahbaz (författare)
- Linköpings universitet,Datorseende,Tekniska högskolan
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- Van de Weijer, Joost (författare)
- Universitat Autonoma de Barcelona, Spain
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- Ali, Sadiq (författare)
- Universitat Autonoma de Barcelona, Spain
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- Felsberg, Michael (författare)
- Linköpings universitet,Datorseende,Tekniska högskolan,Centrum för medicinsk bildvetenskap och visualisering, CMIV
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(creator_code:org_t)
- Berlin, Heidelberg : Springer Berlin/Heidelberg, 2013
- 2013
- Engelska.
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Ingår i: Computer Analysis of Images and Patterns. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642402609 - 9783642402616 ; , s. 154-162
- Relaterad länk:
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https://liu.diva-por... (primary) (Raw object)
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http://liu.diva-port...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- 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.
Nyckelord
- Color
- texture
- image representation
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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