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

A new algorithm for color image comparison based on similarity measures

Authors
Daniel Paternain, Mikel Galar, Aranzazu Jurio, Edurne Barrenechea
Corresponding Author
Daniel Paternain
Available Online August 2013.
DOI
https://doi.org/10.2991/eusflat.2013.88How to use a DOI?
Keywords
Similarity measure Image segmentation Image comparison
Abstract
In this work we address the problem of the quality assessments in the process of color images segmentation. We consider each component of a color image as a fuzzy set and therefore, we propose to use similarity measures (between fuzzy sets) to compare image segmentations. We test three segmentation algorithms, FCM [2], MAP-ML [10]and 2-TUP [19] on Berkeley segmentation database [15] and we evaluate the obtained resuts using our proposal.
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Proceedings
8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
August 2013
ISBN
978-90786-77-78-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/eusflat.2013.88How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Daniel Paternain
AU  - Mikel Galar
AU  - Aranzazu Jurio
AU  - Edurne Barrenechea
PY  - 2013/08
DA  - 2013/08
TI  - A new algorithm for color image comparison based on similarity measures
BT  - 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
PB  - Atlantis Press
SP  - 615
EP  - 621
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2013.88
DO  - https://doi.org/10.2991/eusflat.2013.88
ID  - Paternain2013/08
ER  -