A suitable feature vector for images
Feature extraction is basically reducing the amount of resources required to describe a large set of data. Analysis with a large number of variables (like images) generally requires a big amounts of memory and computation power.
You can start from the simplest and slowly work your way up (in computational requirements) until you reach your desired accuracy.

Start from:

ORB (oriented FAST, rotated robust independent features) -> SURF (speed up robust feature) -> SIFT (scale invariant feature transform) -> OverFeat (Convolutional Network) -> vgg16 ... (There are many more, any neural network model can be used for this)