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Review Article | Open Access

A survey of recent interactive image segmentation methods

Hiba Ramadan1( ), Chaymae Lachqar2, Hamid Tairi1
Department of Informatics, Faculty of Sciences Dhar El Mahraz, University of Sidi Mohamed Ben Abdellah, Fez 30000, Morocco
Faculty of Medicine and Pharmacy, University of Sidi Mohamed Ben Abdellah, Fez 30000, Morocco
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Abstract

Image segmentation is one of the most basic tasks in computer vision and remains an initial step of many applications. In this paper, we focus on interactive image segmentation (IIS), often referred to as foreground-background separation or object extraction, guided by user interaction. We provide an overview of the IIS literature by covering more than 150 publications, especially recent works that have not been surveyed before. Moreover, we try to give a comprehensive classification of them according to different viewpoints and present a general and concise comparison of the most recent published works. Furthermore, we survey widely used datasets, evaluation metrics, and available resources in the field of IIS.

Keywords

interactive image segmentationuser interactionlabel propagationdeep learningsuperpixels

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Computational Visual Media
Volume 6 Issue 4,
December 2020
Pages 355-384
DOI: 10.1007/s41095-020-0177-5

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Cite this article:
Ramadan H, Lachqar C, Tairi H. A survey of recent interactive image segmentation methods. Computational Visual Media, 2020, 6(4): 355-384. https://doi.org/10.1007/s41095-020-0177-5

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Received: 12 March 2020
Accepted: 29 April 2020
Published: 22 August 2020
© The Author(s) 2020

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