A Novel Strategy for Designing Efficient Multiple Classifier

  • Rohit Singh
  • Sandeep Samal
  • Tapobrata Lahiri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)

Abstract

In this paper we have shown that systematic incorporation of decision from various classifiers following a simple decision decomposition rule, gives better decision in comparison to the existing multiple classifier systems. In our method each classifier were graded according to their effectiveness of providing more accurate results. This approach first utilizes the best classifier. If this classifier classifies the test sample into more than one class or fails to classify the test data then the feature next to the best is summoned to finish up the remaining part of the classification. The continuation of this process, along with the judicious selection of classifiers, yields better efficiency in identifying a single class for the test data. The results obtained after the experiments on a set of fingerprint images shows the effectiveness of our proposed classifier.

Keywords

Wavelet Coefficient Input Pattern Multiple Classifier Class Boundary Class Center 
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 2005

Authors and Affiliations

  • Rohit Singh
    • 1
  • Sandeep Samal
    • 2
  • Tapobrata Lahiri
    • 3
  1. 1.Wipro TechnologiesBangaloreIndia
  2. 2.Tata Consultancy ServicesBangalore
  3. 3.Indian Institute of Information TechnologyAllahabadIndia

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