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# Finding matching points between two 2d point sets, but different sizes

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Doogie on 25 Feb 2021
Commented: Doogie on 26 Feb 2021
I am trying to find the way of identifying matching points between two sets (they are xy coordinates from two shifted images). Their sizes are different. Both sets have many points that are not shared. In other words, I look for algoriths to find same points between two shifted 2D point sets, which are not identical.
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Doogie on 25 Feb 2021
If we just use closest distance criteria, that wouldn't work because images from which points are collected are drifted from each other.

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### Answers (3)

weikang zhao on 25 Feb 2021
if you dont need a very precise result,
clear
load('xy1.mat');
load('xy2.mat');
fixdistance=[-0.27,2.3];
newxy1=xy1+fixdistance;
dis=@(x,y) sum((x-y).^2);
result=struct([]);
structcount=1;
for i=1:size(newxy1,1)
for j=1:size(xy2,1)
if dis(xy2(j,:),newxy1(i,:))<0.1
result(structcount).xy1num=i;
result(structcount).xy2num=j;
result(structcount).xy1=xy1(i,:);
result(structcount).xy2=xy2(j,:);
structcount=structcount+1;
end
end
end
the struct result contains the results you need. If you need a more general and more accurate method to deal with a large number of similar problems, you need to design an algorithm to estimate fixdistance.
have fun!
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Doogie on 25 Feb 2021
How to estimate fixdistance was my question. Thank you for your nice rephasement

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weikang zhao on 26 Feb 2021
I provide a feasible solution. Assuming that the length of xy1&`xy2` are m and n, first generate a set of size m*n, including the distance between any pair of points, and then deploy a clustering algorithm or GMM fitting algorithm, the cluster center is the fixdistance.
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weikang zhao on 26 Feb 2021
The two sets you provided

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KSSV on 26 Feb 2021
Read about knnsearch.
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Doogie on 26 Feb 2021
I read knnsearch. Simply running knnsearch(xy1, xy2) gives a result. However, I don't thinkt this is what I want. Do I have a misunderstanding? Or could we apply this idea for measuring similiarity between two point sets?

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