TY  - CONF
AU  - Fahad Shahbaz Khan
AU  - Joost Van de Weijer
AU  - Sadiq Ali
AU  - Michael Felsberg
A2  - CAIP
PY  - 2013//
TI  - Evaluating the impact of color on texture recognition
BT  - 15th International Conference on Computer Analysis of Images and Patterns
SP  - 154
EP  - 162
VL  - 8047
PB  - Springer Berlin Heidelberg
KW  - Color
KW  - Texture
KW  - image representation
N2  - 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.
SN  - 0302-9743
SN  - 978-3-642-40260-9
L1  - http://refbase.cvc.uab.es/files/KWA2013.pdf
UR  - http://dx.doi.org/10.1007/978-3-642-40261-6_18
N1  - CIC; 600.048
ID  - Fahad Shahbaz Khan2013
ER  -