Authors:
Ehsan Fazl Ersi
and
John Zelek
Affiliation:
University of Waterloo, Canada
Keyword(s):
skin detection, image brightness levels, neighborhood information, local entropy thresholding.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Segmentation and Grouping
Abstract:
Skin detection has application in people retrieval, face detection/tracking, hand detection/tracking and more recently on face recognition. However, most of the currently available methods are not robust enough for dealing with some real-world conditions, such as illumination variation and background noises. This paper describes a novel technique for skin detection that is capable of achieving high performance in complex environments with real-world conditions. Three main contributions of our work are: (i) processing each pixel in different brightness levels for handling the problem of illumination variation, (ii) proposing a fast and simple method for incorporating the neighborhood information in processing each pixel, and (iii) presenting a comparative study on thresholding the skin likelihood map, and employing a local entropy technique for binarizing our skin likelihood map. Experiments on a set of real-world images and the comparison with some state-of-the-art methods validate t
he robustness of our method.
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