Classify Objects Concepts

The Classify Objects step identifies an unknown sample by comparing a set of its significant features to a set of features that conceptually represent classes of known samples. Classification involves two phases:

• Training—Teaches Vision Builder AI the types of samples you want to classify during the classifying phase. You can train any number of samples to create a set of classes, which you later compare to unknown samples during the classification phase. You store the classes in a classifier file. Training might be a one-time process, or it might be an incremental process you repeat to add new samples to existing classes or to create several classes, thus broadening the scope of samples you want to classify.
• Classifying—Identifies an unknown sample in an inspection image into one of the classes you trained. The classifying phase classifies a sample according to how similar the sample features are to the same features of the trained samples.

Typical applications involving classification include the following:

• Sorting—Sorts objects of varied shapes. For example, sorting different mechanical parts on a conveyor belt into different bins.
• Inspections—Inspects objects by assigning each object an identification score and then rejecting objects that do not closely match members of the training set.