A new algorithm for color image comparison based on similarity measures
Daniel Paternain, Mikel Galar, Aranzazu Jurio, Edurne Barrenechea
Available Online August 2013.
- 10.2991/eusflat.2013.88How to use a DOI?
- Similarity measure Image segmentation Image comparison
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 , MAP-ML and 2-TUP  on Berkeley segmentation database  and we evaluate the obtained resuts using our proposal.
- © 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 - 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 -