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In [[size theory]], a '''size pair''' is a pair <math>(M,\varphi)</math>, where <math>M\ </math> is a compact [[topological space]] and <math>\varphi:M\to \mathbb{R}^k</math> is a [[continuous function]]<ref name="FroLa99">Patrizio Frosini, Claudia Landi, ''Size theory as a topological tool for computer vision'', Pattern Recognition And Image Analysis, 9(4):596-603, 1999.</ref><ref>Patrizio Frosini, Michele Mulazzani, | |||
''Size homotopy groups for computation of natural size distances'', | |||
Bulletin of the Belgian Mathematical Society - Simon Stevin, 6:455-464, 1999.</ref> | |||
.<ref>Françoise Dibos, Patrizio Frosini, Denis Pasquignon, | |||
''The use of size functions for comparison of shapes through differential invariants'', | |||
Journal of Mathematical Imaging and Vision, 21(2):107-118, 2004.</ref> | |||
The function <math>\varphi</math> is called a ''[[measuring function]]''. The topological space <math>M\ </math> is usually assumed to be also a [[locally connected]] and [[Hausdorff space]]. | |||
==References== | |||
{{reflist}} | |||
==See also== | |||
* [[Size theory]] | |||
* [[Size function]] | |||
* [[Size functor]] | |||
* [[Size homotopy group]] | |||
* [[Natural pseudodistance]] | |||
[[Category:Differential geometry]] | |||
[[Category:Topology]] |
Revision as of 05:12, 5 September 2012
In size theory, a size pair is a pair , where is a compact topological space and is a continuous function[1][2] .[3] The function is called a measuring function. The topological space is usually assumed to be also a locally connected and Hausdorff space.
References
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See also
- ↑ Patrizio Frosini, Claudia Landi, Size theory as a topological tool for computer vision, Pattern Recognition And Image Analysis, 9(4):596-603, 1999.
- ↑ Patrizio Frosini, Michele Mulazzani, Size homotopy groups for computation of natural size distances, Bulletin of the Belgian Mathematical Society - Simon Stevin, 6:455-464, 1999.
- ↑ Françoise Dibos, Patrizio Frosini, Denis Pasquignon, The use of size functions for comparison of shapes through differential invariants, Journal of Mathematical Imaging and Vision, 21(2):107-118, 2004.