Algorithm for finding visually similar photos from a database?
A valid approach you can consider is the Bag-of-Words model.
Basically you can do an offline computation of the target images. You can extract from those images a bunch of features in order to create a codebook with algorithms like k-means clustering. Searching for the nearest images will lead to the applications of an algorithm like Nearest neighbor search in the space of the codebook.
For the neighbour search you can use FLANN
- http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN
- http://opencv.willowgarage.com/documentation/cpp/flann_fast_approximate_nearest_neighbor_search.html
Take a look also at:Visual similarity search algorithm
This is only a possibility and, truth must be told, this topic is really challenging and litterature on it is really huge.
Just some references:
- http://www.cs.nott.ac.uk/~qiu/webpages/Papers/ColorPatternRecognition.pdf
- http://cs.brown.edu/~th/papers/Hofmann-UAI99.pdf
- http://www.ifp.illinois.edu/~jyang29/ScSPM.htm
- http://johnwinn.org/Publications/papers/Savarese_Winn_Criminisi_Correlatons_CVPR2006.pdf
- http://www-cvr.ai.uiuc.edu/ponce_grp/publication/paper/cvpr06b.pdf
Take a look at http://vision.caltech.edu/malaa/software/research/image-search/ it uses LSH algorithm and some kind of kd-tree.Also this task is called CBIR or image duplicate search.