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I want to search images using their histograms of colors. For extracting these histograms I will use OpenCV, I also found examples which describes how to compare two images using histograms of colors. But I have some issues:

  1. Google and another search-engines uses these histograms for searching by image, but I do not think that they iteratively compare described image with images in the database (as it done in the OpenCV examples). So how can I implement quick image search using histograms?

  2. Can I use for this purpose and another image searching purposes common RDBMS like MySQL?

konstantin_doncov
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  • This question is not really about opencv, image processing, or computer vision. 1) Remember your data structures. You want fast lookup, don't care much about insertion costs -- something using a hash table perhaps? 2) Sure, although if all you need is some kinda of key-value storage, then it may not be the best choice -- some kind of NoSQL store might be more appropriate. Question here is, what are your requirements, how should it scale? – Dan Mašek Nov 26 '16 at 17:42
  • @DanMašek hmm... I think it is relative to computer vision and other due to we need to compare images two by two, and it is very slow. Any hash functions will help only if we need to find exactly desired image, but if even one pixel will be different hash will failure. That is why I asked this question. Please tell me if I wrong with something. – konstantin_doncov Nov 26 '16 at 23:24
  • Ok, I see now that it's actually about finding the target with the least distance from source, so yeah, that wouldn't help. – Dan Mašek Nov 26 '16 at 23:33
  • Actually, check [this question out](http://stackoverflow.com/questions/12952729/how-to-understand-locality-sensitive-hashing). That might provide some leads for research. – Dan Mašek Nov 26 '16 at 23:51

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