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  4. Methodology for Evaluation and Selection of Features
 
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1999
Conference Paper
Title

Methodology for Evaluation and Selection of Features

Abstract
In this paper a methodology for selecting features for the multiclass-problem is discussed. The approach is based on an iterative solution scheme. The two major steps "selection of feature subsets" and "evaluation of their effectiveness" are realized as a sequential forward search strategy combined with the evaluation of the Kullback-Leibler distance in the approximation for normal distributions. Thus, the method becomes computationally very efficient and may be applied to feature pools of up to several hundred primary features. Its effectiveness is demonstrated for a task from the field of texture segmentation.
Author(s)
Pannekamp, J.
Schmutz, M.
Mainwork
Workshop on Texture Analysis 1998. Proceedings  
Conference
Workshop on Texture Analysis (WTA) 1998  
Language
English
Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA  
Keyword(s)
  • Bildverarbeitung

  • evaluation

  • feature selection

  • Kullback-Leibler Distance

  • Merkmalerkennung

  • Sequential Search

  • texture analysis

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