MULTIREGION GRAPH CUT IMAGE SEGMENTATION

Mohamed Ben Salah, Ismail Ben Ayed, Amar Mitiche

2008

Abstract

The purpose of our study is two-fold: (1) investigate an image segmentation method which combines parametric modeling of the image data and graph cut combinatorial optimization and, (2) use a prior which allows the number of labels/regions to decrease when the number of regions is not known and the algorithm initialized with a larger number. Experimental verification shows that the method results in good segmentations and runs faster than conventional graph cut methods.

Paper Citation

in Harvard Style

Ben Salah M., Ben Ayed I. and Mitiche A. (2008). MULTIREGION GRAPH CUT IMAGE SEGMENTATION . In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 535-538. DOI: 10.5220/0001081605350538

in Bibtex Style

@conference{visapp08,
author={Mohamed Ben Salah and Ismail Ben Ayed and Amar Mitiche},
title={MULTIREGION GRAPH CUT IMAGE SEGMENTATION},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={535-538},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001081605350538},
isbn={978-989-8111-21-0},
}

in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - MULTIREGION GRAPH CUT IMAGE SEGMENTATION
SN - 978-989-8111-21-0
AU - Ben Salah M.
AU - Ben Ayed I.
AU - Mitiche A.
PY - 2008
SP - 535
EP - 538
DO - 10.5220/0001081605350538