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Artificial Intelligence Review

Erschienen in:

18.04.2020

Image segmentation evaluation: a survey of methods

verfasst von: Zhaobin Wang, E. Wang, Ying Zhu

Erschienen in: Artificial Intelligence Review | Ausgabe 8/2020

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Abstract

Image segmentation is a prerequisite for image processing. There are many methods for image segmentation, and as a result, a great number of methods for evaluating segmentation results have also been proposed. How to effectively evaluate the quality of image segmentation is very important. In this paper, the existing image segmentation quality evaluation methods are summarized, mainly including unsupervised methods and supervised methods. Based on hot issues, the application of metrics in natural, medical and remote sensing image evaluation is further outlined. In addition, an experimental comparison for some methods were carried out and the effectiveness of these methods was ranked. At the same time, the effectiveness of classical metrics for remote sensing and medical image evaluation is also verified.

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Titel: Image segmentation evaluation: a survey of methods
verfasst von: Zhaobin Wang
E. Wang
Ying Zhu
Publikationsdatum: 18.04.2020
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 8/2020
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-020-09830-9

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