Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)

Convex combination of grouping functions for image thresholding. Selection of weighting vectors

Authors
Aranzazu Jurio, Miguel Pagola, Daniel Paternain, Nicolas Madrid, Humberto Bustince
Corresponding Author
Aranzazu Jurio
Available Online August 2013.
DOI
10.2991/eusflat.2013.48How to use a DOI?
Keywords
Thresholding grouping function convex combination
Abstract

In this work we present a thresholding algorithm for greyscale images. Our proposal is based on the use of grouping functions to find the best threshold. These functions are able to measure the membership of a grey intensity to the background or to the object of the image, so the best threshold is the one associated with the highest grouping value. To avoid the hard task concerning the choice of a suitable grouping function for any given image, we propose to use a combination of several of them. We study different ways of choosing the weights for this combination.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
Series
Advances in Intelligent Systems Research
Publication Date
August 2013
ISBN
978-90786-77-78-9
ISSN
1951-6851
DOI
10.2991/eusflat.2013.48How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Aranzazu Jurio
AU  - Miguel Pagola
AU  - Daniel Paternain
AU  - Nicolas Madrid
AU  - Humberto Bustince
PY  - 2013/08
DA  - 2013/08
TI  - Convex combination of grouping functions for image thresholding. Selection of weighting vectors
BT  - Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
PB  - Atlantis Press
SP  - 334
EP  - 341
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2013.48
DO  - 10.2991/eusflat.2013.48
ID  - Jurio2013/08
ER  -