Authors:
Anderson Carlos Sousa e Santos
and
Helio Pedrini
Affiliation:
University of Campinas, Brazil
Keyword(s):
Skin Detection, Image Analysis, Face Detection, Color Models.
Related
Ontology
Subjects/Areas/Topics:
Color and Texture Analyses
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Segmentation and Grouping
Abstract:
Human skin segmentation has several applications in image and video processing fields, whose main purpose is to distinguish image portions between skin and non-skin regions. Despite the large number of methods available in the literature, accurate skin segmentation is still a challenging task. Many methods rely on color information, which does not completely discriminate the image regions due to variations in lighting conditions and ambiguity between skin and background color. Therefore, there is still need to adapt the segmentation to particular conditions of the images. In contrast to the methods that rely on faces, hands or any other body content detector, we describe a self-contained method for adaptive skin segmentation that makes use of spatial analysis to produce regions from which the overall skin can be estimated. A comparison with state-of-the-art methods using a well known challenging data set shows that our method provides significant improvement on the skin segmentation.