The paper A Neural Algorithm of Artistic Style detailed on how to extract two sets of features from a given image: the content, and and the style.
In convolutional neural networks, each layer stores information in an abstraction based on the previous layer. For example, the first layer may search for dark pixels in a line to represent an edge. The next layer may then look for two perpendicular edges to represent a corner. The last layer can then return a classification based on which of the features are present and how they are arranged.