ICIP 2006, Atlanta, GA
 

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Paper Detail

Paper:WP-P1.5
Session:Visual Object/Event Detection, Segmentation, and Classification
Time:Wednesday, October 11, 14:20 - 17:00
Presentation: Poster
Topic: Image & Video Segmentation: Model-fitting-based methods
Title: SKIN DETECTION IN WEB IMAGERY: COMPARISON OF TECHNIQUES AND PROPOSAL
Authors: Heitor Ramos; Universidade Federal de Alagoas 
 Alejandro Frery; Universidade Federal de Alagoas 
 José Alencar-Neto; Justiça Federal de Primeira Instância 
Abstract: This paper presents a quantitative comparison of the performance of skin detection techniques for a Web-based system. The procedures under analysis employ dimensionality reduction, with or without color correction. We propose a rule for deciding if an image requires color correction and, if needed, which is the best procedure. Geometric rules, parametric methods and histogram-based techniques are compared in terms of accuracy and performance. With the proposed heuristic for color correction, the best performances are achieved by a classifier based on the mixture of two Gaussian laws applied to data projected with principal component analysis and a by a KDD-based rule that operates on the RGB space.