There are some topics here that are very helpful on how to find similar pictures.
What I want to do is to get a fingerprint of a picture and find the same picture on different photos taken by a digital camera. The SURF algorithm seams to be the best way to be independent on scaling, angle and other distortions.
I'm using OpenCV with the SURF algorithm to extract features on the sample image. Now I'm wondering how to convert all this feature data (position, laplacian, size, orientation, hessian) into a fingerprint or hash.
This fingerprint will be stored in a database and a search query must be able to compare that fingerprint with a fingerprint of a photo with almost the same features.
It seems that there is no way to convert all the descriptor vectors into a simple hash. So what would be the best way to store the image descriptors into the database for fast querying?
Would Vocabulary Trees be an option?
I would be very thankful for any help.