Skin detection is an important process in many applications like hand gesture recognition, face detection and ego-vision systems. This paper presents a new skin detection method based on a dynamic generation of the skin cluster range in the YCbCr color space, by taking into account the lighting conditions. The method is based on the identification of skin color clusters in the YCb and YCr subspaces. The experimental results, carried out on two publicly available databases, show that the proposed method is robust against illumination changes and achieves satisfactory results in terms of both qualitative and quantitative performance evaluation parameters.

Dynamic Colour Clustering for Skin Detection Under Different Lighting Conditions

Nadia Brancati;Giuseppe De Pietro;Maria Frucci;Luigi Gallo
2017

Abstract

Skin detection is an important process in many applications like hand gesture recognition, face detection and ego-vision systems. This paper presents a new skin detection method based on a dynamic generation of the skin cluster range in the YCbCr color space, by taking into account the lighting conditions. The method is based on the identification of skin color clusters in the YCb and YCr subspaces. The experimental results, carried out on two publicly available databases, show that the proposed method is robust against illumination changes and achieves satisfactory results in terms of both qualitative and quantitative performance evaluation parameters.
2017
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
978-3-319-54220-1
Skin Detection
Dynamic Clustering
YCbCr colour space
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/329060
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