DocumentCode :
3194336
Title :
Rotation invariant texture feature extraction based on Sorted Neighborhood Differences
Author :
Saipullah, Khairul Muzzammil ; Kim, Deok-Hwan ; Lee, Seok-Lyong
Author_Institution :
Dept. of Electronic Engineering, Inha University, S. Korea
fYear :
2011
fDate :
11-15 July 2011
Firstpage :
1
Lastpage :
6
Abstract :
Rotation invariant texture descriptor plays an important role in texture-based object classification. However the classification accuracy may decrease due to the inconsistent performance of texture descriptor with respect to various rotated angles. In this paper we propose a consistent rotation invariant texture descriptor named Sorted Neighborhood Differences (SND). SND is derived from the integration of sorted neigh- borhood and binary patterns. Experimental results show that overall texture classification accuracy of SND with respect to different rotations using OUTEX TC 0010 texture database is 91.81% whereas those of LBPriu and LBP-HF are 86.42% and 88.28%, respectively. The texture and coin classification accuracies of SND are also consistent in various rotation angles and illumination levels.
Keywords :
Sorted Neighborhood Differences; Texture feature; rotation invariant; texture classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo (ICME), 2011 IEEE International Conference on
Conference_Location :
Barcelona, Spain
ISSN :
1945-7871
Print_ISBN :
978-1-61284-348-3
Electronic_ISBN :
1945-7871
Type :
conf
DOI :
10.1109/ICME.2011.6011907
Filename :
6011907
Link To Document :
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