Compare similarity of images using OpenCV with Python

Question

I\'m trying to compare a image to a list of other images and return a selection of images (like Google search images) of this list with up to 70% of similarity.

I ge

Answer 1

You are embarking on a massive problem, referred to as "content based image retrieval", or CBIR. It's a massive and active field. There are no finished algorithms or standard approaches yet, although there are a lot of techniques all with varying levels of success.

Even Google image search doesn't do this (yet) - they do text-based image search - e.g., search for text in a page that's like the text you searched for. (And I'm sure they're working on using CBIR; it's the holy grail for a lot of image processing researchers)

If you have a tight deadline or need to get this done and working soon... yikes.

Here's a ton of papers on the topic:

http://scholar.google.com/scholar?q=content+based+image+retrieval

Generally you will need to do a few things:

1. Extract features (either at local interest points, or globally, or somehow, SIFT, SURF, histograms, etc.)
2. Cluster / build a model of image distributions

This can involve feature descriptors, image gists, multiple instance learning. etc.