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Data Fusion at Different Levels

  • Marcos Faundez-Zanuy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5398)

Abstract

This paper summarizes the main characteristics of data fusion at different levels (sensor, features, scores and decisions). Although it is presented in the framework of biometric applications it is general for all the pattern recognition applications because this presentation is focused in the main blocks of a general pattern recognition system. Thus, the application in mind will imply a different sensor, feature extractor, classifier and decision maker but data fusion will be performed in a similar way.

Keywords

Data Fusion Opinion Fusion Speaker Recognition Biometric System False Acceptance Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Marcos Faundez-Zanuy
    • 1
  1. 1.Escola Universitària Politècnica de MataróMATARÓ (BARCELONA)Spain

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