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Recall or precision-oriented strategies for binary classification of skin pixels

[+] Author Affiliations
Francesca Gasparini

Universitá degli Studi di Milano-Bicocca, Dipartimento di Informatica, Sistemistica e Comunicazione, Viale Sarca 336, 20126 Milano, Italy

Silvia Corchs

Universitá degli Studi di Milano-Bicocca, Dipartimento di Informatica, Sistemistica e Comunicazione, Viale Sarca 336, 20126 Milano, Italy

Raimondo Schettini

Universitá degli Studi di Milano-Bicocca, Dipartimento di Informatica, Sistemistica e Comunicazione, Viale Sarca 336, 20126 Milano, Italy

J. Electron. Imaging. 17(2), 023017 (May 12, 2008). doi:10.1117/1.2916715
History: Received November 23, 2006; Revised November 05, 2007; Accepted November 15, 2007; Published May 12, 2008
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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.

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© 2008 SPIE and IS&T

Topics

Skin

Citation

Francesca Gasparini ; Silvia Corchs and Raimondo Schettini
"Recall or precision-oriented strategies for binary classification of skin pixels", J. Electron. Imaging. 17(2), 023017 (May 12, 2008). ; http://dx.doi.org/10.1117/1.2916715


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