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 analyze other images and find the position and rotation of that object or similar objects. The object is arbitrarily placed under the camera, but is never scaled and the viewing angle is always 90 degrees.

I have evaluated a commercial library that does exactly what I want: Euresys EasyFind

Below you can find example images of the task at hand. The current implementation uses Feature Detection of OpenCV and is not working flawlessly.

Template:

enter image description here

A match is found for the very same coin:

enter image description here

The match fails for slightly different coins:

enter image description here

The feature detection seems to be the wrong approach. I need to simply the object somehow. But if I do that (Blur, Canny, CornerHarris) feature detection does not work at all.

Any advice for a solid approach is much appreciated. An alternative libary suggestion would be great as well.

c++ opencv pattern-matching
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