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 [11] and 2-TUP [21] on Berkeley segmentation database [17] and we evaluate the obtained results using our proposal.
['Daniel Paternain', 'Mikel Galar', 'Aranzazu Jurio', 'Edurne Barrenechea']
A new algorithm for color image comparison based on similarity measures