Möbius Invariants of Shapes and Images

Identifying when different images are of the same object despite changes caused by imaging technologies, or processes such as growth, has many applications in fields such as computer vision and biological image analysis. One approach to this problem is to identify the group of possible transformatio...

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Veröffentlicht in:Symmetry, Integrability and Geometry: Methods and Applications
Datum:2016
Hauptverfasser: Marsland, S., McLachlan, R.I.
Format: Artikel
Sprache:English
Veröffentlicht: Інститут математики НАН України 2016
Online Zugang:https://nasplib.isofts.kiev.ua/handle/123456789/147846
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Назва журналу:Digital Library of Periodicals of National Academy of Sciences of Ukraine
Zitieren:Möbius Invariants of Shapes and Images / S. Marsland, R.I. McLachlan // Symmetry, Integrability and Geometry: Methods and Applications. — 2016. — Т. 12. — Бібліогр.: 43 назв. — англ.

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Digital Library of Periodicals of National Academy of Sciences of Ukraine
id nasplib_isofts_kiev_ua-123456789-147846
record_format dspace
spelling Marsland, S.
McLachlan, R.I.
2019-02-16T09:14:36Z
2019-02-16T09:14:36Z
2016
Möbius Invariants of Shapes and Images / S. Marsland, R.I. McLachlan // Symmetry, Integrability and Geometry: Methods and Applications. — 2016. — Т. 12. — Бібліогр.: 43 назв. — англ.
1815-0659
2010 Mathematics Subject Classification: 68T45; 68U10
DOI:10.3842/SIGMA.2016.080
https://nasplib.isofts.kiev.ua/handle/123456789/147846
Identifying when different images are of the same object despite changes caused by imaging technologies, or processes such as growth, has many applications in fields such as computer vision and biological image analysis. One approach to this problem is to identify the group of possible transformations of the object and to find invariants to the action of that group, meaning that the object has the same values of the invariants despite the action of the group. In this paper we study the invariants of planar shapes and images under the Möbius group PSL(2,C), which arises in the conformal camera model of vision and may also correspond to neurological aspects of vision, such as grouping of lines and circles. We survey properties of invariants that are important in applications, and the known Möbius invariants, and then develop an algorithm by which shapes can be recognised that is Möbius- and reparametrization-invariant, numerically stable, and robust to noise. We demonstrate the efficacy of this new invariant approach on sets of curves, and then develop a Möbius-invariant signature of grey-scale images.
This research was supported by the Marsden Fund, and RM by a James Cook Research Fellowship, both administered by the Royal Society of New Zealand. SM would like to thank the Erwin Schr¨odinger International Institute for Mathematical Physics, Vienna, where some of this research was performed.
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Інститут математики НАН України
Symmetry, Integrability and Geometry: Methods and Applications
Möbius Invariants of Shapes and Images
Article
published earlier
institution Digital Library of Periodicals of National Academy of Sciences of Ukraine
collection DSpace DC
title Möbius Invariants of Shapes and Images
spellingShingle Möbius Invariants of Shapes and Images
Marsland, S.
McLachlan, R.I.
title_short Möbius Invariants of Shapes and Images
title_full Möbius Invariants of Shapes and Images
title_fullStr Möbius Invariants of Shapes and Images
title_full_unstemmed Möbius Invariants of Shapes and Images
title_sort möbius invariants of shapes and images
author Marsland, S.
McLachlan, R.I.
author_facet Marsland, S.
McLachlan, R.I.
publishDate 2016
language English
container_title Symmetry, Integrability and Geometry: Methods and Applications
publisher Інститут математики НАН України
format Article
description Identifying when different images are of the same object despite changes caused by imaging technologies, or processes such as growth, has many applications in fields such as computer vision and biological image analysis. One approach to this problem is to identify the group of possible transformations of the object and to find invariants to the action of that group, meaning that the object has the same values of the invariants despite the action of the group. In this paper we study the invariants of planar shapes and images under the Möbius group PSL(2,C), which arises in the conformal camera model of vision and may also correspond to neurological aspects of vision, such as grouping of lines and circles. We survey properties of invariants that are important in applications, and the known Möbius invariants, and then develop an algorithm by which shapes can be recognised that is Möbius- and reparametrization-invariant, numerically stable, and robust to noise. We demonstrate the efficacy of this new invariant approach on sets of curves, and then develop a Möbius-invariant signature of grey-scale images.
issn 1815-0659
url https://nasplib.isofts.kiev.ua/handle/123456789/147846
citation_txt Möbius Invariants of Shapes and Images / S. Marsland, R.I. McLachlan // Symmetry, Integrability and Geometry: Methods and Applications. — 2016. — Т. 12. — Бібліогр.: 43 назв. — англ.
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first_indexed 2025-12-07T20:17:07Z
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