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

Francesca Gasparini; Silvia Corchs; Raimondo Schettini

doi:10.1117/1.2916715

1 April 2008 Recall or precision-oriented strategies for binary classification of skin pixels

Francesca Gasparini, Silvia Corchs, Raimondo Schettini

Author Affiliations +

Journal of Electronic Imaging, Vol. 17, Issue 2, 023017 (April 2008). https://doi.org/10.1117/1.2916715

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.

©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Francesca Gasparini, Silvia Corchs, and Raimondo Schettini "Recall or precision-oriented strategies for binary classification of skin pixels," Journal of Electronic Imaging 17(2), 023017 (1 April 2008). https://doi.org/10.1117/1.2916715

Published: 1 April 2008

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available