I have a reference b/w image that contains a reference object (a coin for example). The object is marked by the user, that is the region of interest.
Now I want to
I believe that what would work best for you is some version of brute-force search, similar to cvMatchTemplate
. All feature-extraction-based searches are quite noise-sensitive; unless you have some a-priori reason to know that certain types of features are going to be prominent in all of the images of interest (for example: outline circles/ovals for coins), then feature extraction is unlikely to give you good performance. The problem with brute-force matching is that it is scale and rotation sensitive. Perhaps you can look at the literature for scale-free matching, and/or brute-force possible scales and rotations as well. For the example image you gave, it would actually match itself pretty well if rotated by a few degrees and scaled by a few percent; you "only" need a few hundred calls to cvMatchTemplate
to find a rotated, scaled version.