What is Pattern Recognition?

In many applications, artificial systems perform complex decisions. Crisp formal decisions cannot be often easily defined due to measurement noise or problem ambiguity (e.g. how to decide if the potato in the image is rotten?). However, even in such situations correct decisions may be given by the experts (What potatoes are rotten or healthy.). Pattern recognition aims at designing artificial decision making systems by learning from observations.

Typical examples of pattern recognition applications are optical character recognition (OCR), fingerprint identification, industrial sorting, quality control, license plate recognition, or medical diagnostics.