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Published in:
2005 | OriginalPaper | Chapter
Image Segmentation Evaluation by Techniques of Comparing Clusterings
Authors : Xiaoyi Jiang, Cyril Marti, Christophe Irniger, Horst Bunke
Published in: Image Analysis and Processing – ICIAP 2005
Publisher: Springer Berlin Heidelberg
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The task considered in this paper is performance evaluation of region segmentation algorithms in the ground truth (GT) based paradigm. Given a machine segmentation and a GT reference, performance measures are needed. We propose to consider the image segmentation problem as one of data clustering and, as a consequence, to use measures for comparing clusterings developed in statistics and machine learning. By doing so, we obtain a variety of performance measures which have not been used before in computer vision. In particular, some of these measures have the highly desired property of being a metric. Experimental results are reported on both synthetic and real data to validate the measures and compare them with others.