A new algorithm for color image comparison based on similarity measures

DOI

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.

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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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  - Proceedings of the 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  - 10.2991/eusflat.2013.88
ID  - Paternain2013/08
ER  -