CODEWITHSUNDEEP
pythonopencv
user601836
user601836

Reputation: 3235

image comparison using edges and textures

I am working with python and opencv on a piece of software which should compare two images and return as result a value representing their similarity.

I tried first with histograms, and then with SIFT and SURF but the first method is not localized while the second and the third are slow and do not fit very much with my datased content (mostly pictures of crowds).

I would avoid people detector, so I would like to apply some algorithm connected to edges and textures comparison. Cany you give some hints or online resource?

Upvotes: 0

Views: 1396

Answers (2)

hjweide
hjweide

Reputation: 12523

This is an interesting, although challenging problem! Recently, I came across an article by the University of California, San Diego's Vision Group about classifying scenes of crowds. Here is the link: Urban Tribes: Analyzing Group Photos from a Social Perspective.

As you can see, there is no one-size-fits-all solution, but I would think that this should provide you a good place to start from.

Upvotes: 2

LovaBill
LovaBill

Reputation: 5139

What you're asking is a general image classification framework. Try googling: image classification, scene classification, image Indexing and Retrieval.

In most cases, you'll have to use a multimodal descriptor. Use color, texture, entropy, keypoints, edge histograms.

You can read this and try that.

Upvotes: 1

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