Feature extraction using the Bhattacharyya distance

Research output: Contribution to journalConference article

7 Citations (Scopus)

Abstract

The Bhattacharyya distance provides a valuable information in determining the effectiveness of a feature set and has been used as separability measure for feature selection. Recently, it is shown that it is feasible to predict the classification error accurately using the Bhattacharyya distance. The new formula makes it possible to estimate classification error between two classes within 1-2% margin. In this paper, we propose a new feature extraction method utilizing the result. Initially, we start with an arbitrary feature vector. Assuming that the feature vector is used for classification, we estimate the classification error using the error estimation formula. Then we move the feature vector slightly in the direction so that the estimated classification error is decreased most rapidly. This can be done by taking gradient. Experiments show that the proposed method compare favorably with the conventional methods.

Original languageEnglish
Pages (from-to)2147-2150
Number of pages4
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume3
Publication statusPublished - 1997 Dec 1

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Feature extraction
Error analysis
Experiments

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Control and Systems Engineering

Cite this

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title = "Feature extraction using the Bhattacharyya distance",
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Feature extraction using the Bhattacharyya distance. / Lee, Chulhee; Hong, Daesik.

In: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Vol. 3, 01.12.1997, p. 2147-2150.

Research output: Contribution to journalConference article

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