2D subimage detection in Open CV

Question

What\'s the most sensible algorithm, or combination of algorithms, to be using from OpenCV for the following problem:

• I have a set of small 2D images. I want t

Answer 1

What you need is something like SIFT or SURF.

Answer 2

1. cvMatchTemplate uses a MSE (SQDIFF/SQDIFF_NORMED) kind of metric for the matching. This kind of metric will penalize different alpha values severly (due to the square in the equation). Have you tried normalized cross-correlation? It is known to model linear variations in pixel intensities better.
2. If NCC does not do the job, you will need to transform the images to a space where the intensity differences do not have much effect. e.g. Compute a edge-strength image (canny, sobel etc) and run cvMatchTemplate on these images.
3. Considering the large difference in scales of the images (~10x). A image pyramid will have to be employed to figure out the correct scale for the matching. Recommend you start with a scale (2^1/x: x being the correct scale) and propagate the estimate up the pyramid.