The workflow involves the following steps: 

Dividing an image into segments

Computing various attributes for the segments

Creating several new classes

Interactively assigning segments (called training samples) to each class

Classifying the entire image with a K Nearest Neighbor (KNN), Support Vector Machine (SVM), or Principal Components Analysis (PCA) supervised classification method, based on your training samples.

Exporting the classes to a shapefile or classification image.