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Hmmm, you could warp your images and compute how much they overlap and build a score out of that.
Alternatively you can use a Bag of Words (BoW) approach (see http://answers.opencv.org/question/8677/image-comparison-with-a-database#8686), where you can group your feature vectors to form one BoW-descriptor. Afaik, there doesn't exist THE similarity score between these descriptors. But you can compare them with your favorite histogram-comparison-method (http://docs.opencv.org/modules/imgproc/doc/histograms.html?highlight=comparehist#comparehist) and derive a similarity score out of it. If you find sth else please report back.
