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