Sorry to take so long to reply, I was working through the code and thinking about implementation. Nifty idea, but not I do not believe practical for my situation. I have 7 ROIs, each could contain as many as 10 points, and of those ten the true point may or may not exist. So coming up with all of the possible combinations/permutations could make this solution prohibitive.

I have been thinking about filtering by point instead of collection (at least initially). For good registration, I need at least 4 points. Knowing the distance between the points I can work through each of the points and check the distance between each of the other points. If I set some tolerance, then I can discriminate the points that are not within the tolereance for at least 4 of the 6 distances. This should be fairly quick { 6 distances per point max ~ 10 points per ROI => 420 checks, and if I splice the array for the ROI then this number should decrease as bad points are thrown out. }


If I can run a few tests then I will see what we typically have left. If it is only 1-3 points per ROI then your solution is much more viable.


Quick question (I have not looked for this yet, thought of it while writting), do you or does anyone know of a good module for doing the permutations I need? i.e. N arrays with M elements, creating new unique arrays containing only 1 element from each of the N arrays? I am sure that it is out there, I will look for it tonight.

Thanks for you help,


Cameron

In reply to Re^2: Interesting problem fitting points to a template (algorithm?) by doowah2004
in thread Interesting problem fitting points to a template (algorithm?) by doowah2004

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