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2016 | OriginalPaper | Chapter

Resolution-Independent Superpixels Based on Convex Constrained Meshes Without Small Angles

Authors : Jeremy Forsythe, Vitaliy Kurlin, Andrew Fitzgibbon

Published in: Advances in Visual Computing

Publisher: Springer International Publishing

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Abstract

The over-segmentation problem for images is studied in the new resolution-independent formulation when a large image is approximated by a small number of convex polygons with straight edges at subpixel precision. These polygonal superpixels are obtained by refining and extending subpixel edge segments to a full mesh of convex polygons without small angles and with approximation guarantees. Another novelty is the objective error difference between an original pixel-based image and the reconstructed image with a best constant color over each superpixel, which does not need human segmentations. The experiments on images from the Berkeley Segmentation Database show that new meshes are smaller and provide better approximations than the state-of-the-art.

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previous chapter Image Enhancement by Volume Limitation in Binary Tomography
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Metadata
Title
Resolution-Independent Superpixels Based on Convex Constrained Meshes Without Small Angles
Authors
Jeremy Forsythe
Vitaliy Kurlin
Andrew Fitzgibbon
Copyright Year
2016
Book
Advances in Visual Computing

Print ISBN: 978-3-319-50834-4

Electronic ISBN: 978-3-319-50835-1

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-50835-1_21

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