Evaluating the Impact of Color on Texture Recognition
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 (Refereed)
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.
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 8047
Color, texture, image representation
Engineering and Technology
IdentifiersURN: 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 (online)OAI: oai:DiVA.org:liu-105460DiVA: diva2:707460
15th International Conference on Computer Analysis of Images and Patterns (CAIP 2013), York, UK, 27-29 August 2013
ProjectsCUAS , ELLIT