Features used by the classifier are identified in three steps. First, types of image features associated with image defects are studied using a small set of concept exploration data. Secondly, preliminary measurements for the features are constructed along with the initial version of the classifier's logic. Finally, a training dataset is formed and from there, the final form of the features' metrics as well as the classifier rules are determined.