Introduction to Pattern Recognition


“Pattern recognition is the research area that studies the operation and design of systems that recognize patterns in data. It encloses subdisciplines like discriminant analysis, feature extraction, error estimation, cluster analysis (together sometimes called statistical pattern recognition), grammatical inference and parsing (sometimes called syntactical pattern recognition).              .

… Pattern Recognition Group at Delft University of Technology

description of their research area.

“A branch of artificial intelligence concerned with the classification or description of observations. Pattern recognition aims to classify data (patterns) based on either a priori knowledge or on statistical information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space.”   …. FOLDOC

Pattern recognition is the assignment of some sort of output value (or label) to a given input value (or instance), according to some specific algorithm. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes (for example, determine whether a given email is “spam” or “non-spam”).

Source: wikipedia

Pattern Recognition / Pattern Matching are not same.Pattern recognition algorithms generally aim to provide a reasonable answer for all possible inputs and to do “fuzzy” matching of inputs. This is opposed to pattern matching algorithms, which look for exact matches in the input with pre-existing patterns.