DocumentCode :
3257042
Title :
Adaptive windowing and granular computing based image segmentation
Author :
Srikumar, Satyabrat ; Wagh, Mamta ; Nanda, P.K.
Author_Institution :
Dept. of Comput. Sci. Eng., Siksha `O´´ Anusandhan Univ., Bhubaneswar, India
fYear :
2011
fDate :
28-30 Dec. 2011
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, adaptive windowing based segmentation scheme has been proposed. The image has been partitioned into different windows and the windows to be segmented, have been fixed by three criteria. The first one is based on pyramid approach where, the preselected windows are merged based on entropy measure. The second one is based on incremental window selection method. In the third criterion, the preselected windows are merged based on entropy measure. The windows thus fixed are considered as sub-images and each sub-image has been segmented based on the notion of rough entropy and granular computing. The algorithm could segment the images with uneven lighting condition.
Keywords :
granular computing; image segmentation; adaptive windowing; entropy measurement; granular computing; image segmentation; preselected windows; pyramid approach; Approximation methods; Computational efficiency; Entropy; Image segmentation; Lighting; Merging; Rough sets; Adaptive Windowing; Granular Computing; Rough Set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Energy, Automation, and Signal (ICEAS), 2011 International Conference on
Conference_Location :
Bhubaneswar, Odisha
Print_ISBN :
978-1-4673-0137-4
Type :
conf
DOI :
10.1109/ICEAS.2011.6147097
Filename :
6147097
Link To Document :
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