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Journal of Electronic Imaging

Interactive segmentation: a scalable superpixel-based method
Author(s): Bérengère Mathieu; Alain Crouzil; Jean-Baptiste Puel
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Paper Abstract

This paper addresses the problem of interactive multiclass segmentation of images. We propose a fast and efficient new interactive segmentation method called superpixel α fusion (SαF). From a few strokes drawn by a user over an image, this method extracts relevant semantic objects. To get a fast calculation and an accurate segmentation, SαF uses superpixel oversegmentation and support vector machine classification. We compare SαF with competing algorithms by evaluating its performances on reference benchmarks. We also suggest four new datasets to evaluate the scalability of interactive segmentation methods, using images from some thousand to several million pixels. We conclude with two applications of SαF.

Paper Details

Date Published: 26 September 2017
PDF: 18 pages
J. Electron. Imag. 26(6) 061606 doi: 10.1117/1.JEI.26.6.061606
Published in: Journal of Electronic Imaging Volume 26, Issue 6
Show Author Affiliations
Bérengère Mathieu, Institut de Recherche en Informatique de Toulouse (France)
Alain Crouzil, Institut de Recherche en Informatique de Toulouse (France)
Jean-Baptiste Puel, Ecole Nationale Supérieure de Formation de l'Enseignement Agricole (France)


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