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Journal of Electronic Imaging

Recall or precision-oriented strategies for binary classification of skin pixels
Author(s): Francesca Gasparini; Silvia Corchs; Raimondo Schettini
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Paper Abstract

Skin detection is a preliminary step in many applications. We analyze some of the most frequently cited binary skin classifiers based on explicit color cluster definition and present possible strategies to improve their performance. In particular, we demonstrate how this can be accomplished by using genetic algorithms to redefine the cluster boundaries. We also show that the fitness function can be tuned to favor either recall or precision in pixel classification. Some combining strategies are then proposed to further improve the performance of these binary classifiers in terms of recall or precision. Finally, we show that, whatever the method or the strategy employed, the performance can be enhanced by preprocessing the images with a white balance algorithm. All the experiments reported here have been run on a large and heterogeneous image database.

Paper Details

Date Published: 1 April 2008
PDF: 15 pages
J. Electron. Imaging. 17(2) 023017 doi: 10.1117/1.2916715
Published in: Journal of Electronic Imaging Volume 17, Issue 2
Show Author Affiliations
Francesca Gasparini, Univ. degli Studi di Milano-Bicocca (Italy)
Silvia Corchs, Univ. degli Studi di Milano-Bicocca (Italy)
Raimondo Schettini, Univ. degli Studi di Milano-Bicocca (Italy)

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