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In [[mathematics]], the '''matching distance'''<ref name="dAFrLa06">Michele d'Amico, Patrizio Frosini, Claudia Landi, ''Using matching distance in Size Theory: a survey'', International Journal of Imaging Systems and Technology, 16(5):154–161, 2006.</ref><ref name="dAFrLa10">Michele d'Amico, Patrizio Frosini, Claudia Landi, ''Natural pseudo-distance and optimal matching between reduced size functions'', Acta Applicandae Mathematicae, 109(2):527-554, 2010.</ref> is a [[metric (mathematics)|metric]] on the space of [[size function]]s.
 
[[Image:DistMatchWiki1.png|thumb|500px|Example: The matching distance between <math>\ell_1=r+a+b</math> and <math>\ell_2=r'+a'</math> is given by <math>d_\text{match}(\ell_1, \ell_2)=\max\{\delta(r,r'),\delta(b,a'),\delta(a,\Delta)\}=4</math>]]
 
The core of the definition of matching distance is the observation that the
information contained in a size function can be combinatorially stored in a formal series of lines and points of the plane, called respectively ''[[size function|cornerlines]]''  and ''[[size function|cornerpoints]]''.
 
Given two size functions <math>\ell_1</math> and <math>\ell_2</math>, let  <math>C_1</math> (resp. <math>C_2</math>) be the multiset of
all cornerpoints and cornerlines for <math>\ell_1</math> (resp. <math>\ell_2</math>) counted with their
multiplicities, augmented by adding a countable infinity of points  of the
diagonal <math>\{(x,y)\in \R^2: x=y\}</math>.
 
The ''matching distance'' between <math>\ell_1</math> and <math>\ell_2</math> is given by
<math>d_\text{match}(\ell_1, \ell_2)=\min_\sigma\max_{p\in C_1}\delta (p,\sigma(p))</math>
where <math>\sigma</math> varies among all the bijections between <math>C_1</math> and <math>C_2</math> and
 
: <math>\delta\left((x,y),(x',y')\right)=\min\left\{\max \{|x-x'|,|y-y'|\}, \max\left\{\frac{y-x}{2},\frac{y'-x'}{2}\right\}\right\}.</math>
 
Roughly speaking, the matching distance <math>d_\text{match}</math>
between two size functions is the minimum, over all the matchings
between the cornerpoints of the two size functions, of the maximum
of the <math>L_\infty</math>-distances between two matched cornerpoints. Since
two size functions can have a different number of cornerpoints,
these can be also matched to points of the diagonal <math>\Delta</math>. Moreover, the definition of <math>\delta</math> implies that matching two points of the diagonal has no cost.
 
==References==
{{Reflist}}
 
==See also==
* [[Size theory]]
* [[Size function]]
* [[Size functor]]
* [[Size homotopy group]]
* [[Natural pseudodistance]]
 
{{DEFAULTSORT:Matching Distance}}
[[Category:Topology]]

Latest revision as of 13:47, 28 August 2013

In mathematics, the matching distance[1][2] is a metric on the space of size functions.

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Example: The matching distance between 1=r+a+b and 2=r+a is given by dmatch(1,2)=max{δ(r,r),δ(b,a),δ(a,Δ)}=4

The core of the definition of matching distance is the observation that the information contained in a size function can be combinatorially stored in a formal series of lines and points of the plane, called respectively cornerlines and cornerpoints.

Given two size functions 1 and 2, let C1 (resp. C2) be the multiset of all cornerpoints and cornerlines for 1 (resp. 2) counted with their multiplicities, augmented by adding a countable infinity of points of the diagonal {(x,y)2:x=y}.

The matching distance between 1 and 2 is given by dmatch(1,2)=minσmaxpC1δ(p,σ(p)) where σ varies among all the bijections between C1 and C2 and

δ((x,y),(x,y))=min{max{|xx|,|yy|},max{yx2,yx2}}.

Roughly speaking, the matching distance dmatch between two size functions is the minimum, over all the matchings between the cornerpoints of the two size functions, of the maximum of the L-distances between two matched cornerpoints. Since two size functions can have a different number of cornerpoints, these can be also matched to points of the diagonal Δ. Moreover, the definition of δ implies that matching two points of the diagonal has no cost.

References

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See also

  1. Michele d'Amico, Patrizio Frosini, Claudia Landi, Using matching distance in Size Theory: a survey, International Journal of Imaging Systems and Technology, 16(5):154–161, 2006.
  2. Michele d'Amico, Patrizio Frosini, Claudia Landi, Natural pseudo-distance and optimal matching between reduced size functions, Acta Applicandae Mathematicae, 109(2):527-554, 2010.