Find Exact Matches of SURF in openCV

Question

I am using openCV Surf tracker to find exact points in two images. as you know, Surf returns many Feature points in both images. what i want to do is using these feature parameters to find out which matches are exactly correct (true positive matches). In my application i need only true positive matches.

These parameters existed : Hessian, Laplacian, Distance, Size, Dir.

I dont know how to use these parameters? is exact matches have less distance or more hessian? laplacian can help ? size or dir can help ?

How can i find Exact matches(true positives)??

Answer 1

Hi

The answer which I'm about to post is just my guess bcz I have not tested it to see whether it exactly works as predicted or not. By comparing the relative polar distance between 3 random candidate feature points returned by opencv and comparing it with the counterpart points in the template (with a certain error), you can not only compute the probability of true positiveness, but also the angle and the scale of your matched pattern.

Cheers

Answer 2

It obvious you can't be 100% sure which points truly match. You can increase (in the cost of performance) positives by tuning SURF parameters (see some links here). Depending on your real task you can use robust algorithms to eliminate outliers, i.e. RANSAC if you perform kind of model fitting. Also, as Erfan said, you can use spatial information (you can easily find articles on this topic).