Image segmentation is the first stage of processing in many practical computer vision systems. While development of particular segmentation algorithms has attracted considerable research interest, relatively little work has been published on the subject of their evaluation. In this paper we propose a framework for quantitative evaluation of segmentation algorithms which we believe addresses shortcomings of previous approaches, and use this framework to compare several state-of-the-art algorithms.
|Translated title of the contribution
|Evaluating image segmentation algorithms using monotonic hulls in fitness/cost space
|Title of host publication
|Tim Cootes, Chris Taylor
|363 - 372
|Number of pages
|Published - Sept 2001