Image Segmentation Evaluation by Techniques of Comparing Clusterings

Autor:	Horst Bunke, Cyril Marti, Xiaoyi Jiang, Christophe Irniger
Rok vydání:	2005
Předmět:	Ground truth Computer science business.industry Segmentation-based object categorization Scale-space segmentation Image processing Image segmentation Machine learning computer.software_genre Metric (mathematics) Segmentation Artificial intelligence business Cluster analysis computer
Zdroj:	Image Analysis and Processing – ICIAP 2005 ISBN: 9783540288695 ICIAP
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::54cbe881d9d9ee7f794f073a9a5e5349 https://doi.org/10.1007/11553595_42 Zobrazit plný text záznamu