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Pattern Recognition Theory and Applications pp 1–19Cite as

Advances in Statistical Pattern Recognition

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Part of the book series: NATO ASI Series ((NATO ASI F,volume 30))

Abstract

Statistical pattern recognition is now a mature discipline which has been successfully applied in several application domains. The primary goal in statistical pattern recognition is classification, where a pattern vector is assigned to one of a finite number of classes and each class is characterized by a probability density function on the measured features. A pattern vector is viewed as a point in the multidimensional space defined by the features. Design of a recognition system based on this paradigm requires careful attention to the following issues: type of classifier (single-stage vs. hierarchical), feature selection, estimation of classification error, parametric vs. nonparametric decision rules, and utilizing contextual information. Current research emphasis in pattern recognition is on designing efficient algorithms, studying small sample properties of various estimators and decision rules, implementing the algorithms on novel computer architecture, and incorporating context and domain-specific knowledge in decision making.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Michigan State University, 48824, East Lansing, Michigan, USA

    Anil K. Jain

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  1. Anil K. Jain
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Editors and Affiliations

  1. Philips Research Laboratory, Avenue Em. Van Becelaere 2, Box 8, B-1170, Brussels, Belgium

    Pierre A. Devijver

  2. Department of Electronic and Electrical Engineering, University of Surrey, GU2 5XH, Guildford, UK

    Josef Kittler

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© 1987 Springer-Verlag Berlin Heidelberg

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Jain, A.K. (1987). Advances in Statistical Pattern Recognition. In: Devijver, P.A., Kittler, J. (eds) Pattern Recognition Theory and Applications. NATO ASI Series, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83069-3_1

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  • DOI: https://doi.org/10.1007/978-3-642-83069-3_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-83071-6

  • Online ISBN: 978-3-642-83069-3

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