Pattern recognition

For the William Gibson novel, see: Pattern Recognition (novel).

Pattern recognition (also known as classification or pattern classification) is a field within the area of computer science and can be defined as "the act of taking in raw data and taking an action based on the category of the data" [1]. It uses methods from statistics, machine learning and other areas.

Typical applications are automatic speech recognition, classification of text into several categories (e.g. spam/non-spam email messages), the automatic recognition of handwritten postal codes on postal envelopes, or the automatic recognition of images of human faces. The last three examples form the subtopic image analysis of pattern recognition that deals with digital images as input to pattern recognition systems.

Pattern recognition techniques

• Neural Networks
• Hidden Markov Models
• Bayesian networks

Application domains

• computer vision
• machine vision
• medical image analysis
• optical character recognition
• credit scoring

See also:

• artificial intelligence
• machine learning
• barcode
• information retrieval
• color histograms

References

1. Richard O. Duda, Peter E. Hart, David G. Stork (2001) Pattern classification (2nd edition), Wiley, New York, ISBN 0471056693.
2. J. Schuermann: Pattern Classification: A Unified View of Statistical and Neural Approaches, Wiley&Sons, 1996, ISBN 0471135348

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