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Improved GrabCut Technique for Segmentation of Color Image

Published on February 2014 by Basavaprasad B., Ravindra S. Hegadi
journal_cover_thumbnail

National Conference on Recent Advances in Information Technology
Foundation of Computer Science USA
NCRAIT - Number 1
February 2014
Authors: Basavaprasad B., Ravindra S. Hegadi
28e930b3-4831-4eed-942b-d20dd20eb785

Basavaprasad B., Ravindra S. Hegadi . Improved GrabCut Technique for Segmentation of Color Image. National Conference on Recent Advances in Information Technology. NCRAIT, 1 (February 2014), 5-8.

@article{
author = { Basavaprasad B., Ravindra S. Hegadi },
title = { Improved GrabCut Technique for Segmentation of Color Image },
journal = { National Conference on Recent Advances in Information Technology },
issue_date = { February 2014 },
volume = { NCRAIT },
number = { 1 },
month = { February },
year = { 2014 },
issn = 0975-8887,
pages = { 5-8 },
numpages = 4,
url = { /proceedings/ncrait/number1/15137-1402/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Recent Advances in Information Technology
%A Basavaprasad B.
%A Ravindra S. Hegadi
%T Improved GrabCut Technique for Segmentation of Color Image
%J National Conference on Recent Advances in Information Technology
%@ 0975-8887
%V NCRAIT
%N 1
%P 5-8
%D 2014
%I International Journal of Computer Applications
Abstract

An improved method of the GrabCut Technique has been implemented in this paper which works on image segmentation quite interactively and user friendly and which reduces the user effort. This paper emphasizes on modification of GrabCut image segmentation which is an iterative algorithm that combines statistics and Graph Cut in order to accomplish detailed image segmentation with proper input. The proposed algorithm requires an initial selection of object to be segmented. The algorithm will deflate to capture the object of interest, which has different image feature as compared to its background. This algorithm does not need any more user intervention during its segmentation process. The proposed algorithm could achieve an effective segmentation of objects from background for different classes of images.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Grabcut Graph Cut Gmm Color Clustering Border-matting Energy Minimization Foreground Background Gibbs Energy Alpha Matting Optimization.