What is commonly used for features when classifying images with nearest neighbor algorithms?

If one wanted to perform the K-nearest-neighbors algorithm to do classification on im开发者_如何学Pythonages, how are features extracted from the images? What are the easiest, most effective methods?

Great tutorial on feature learning for image classification

It really depends on the exact problems.

For general problems, I'd always start with either some form of texture features (if you want image-level features) or local features (such as SURF).

The documentation for mahotas has a bit of an intro into this.

There are many features you can use... but as already said it depends on the case and what you get from your segmentations...

you can classify from:

color
rectangularity
circularity
area
diameter
circumference
...

these are just a few but should be easy to calculate once you segmented your objects...

Hope that helps...