Segmenting Hands of Arbitrary Color

Colorhasbeen widelyused for handsegmentation. However, many approaches rely on predefined skin color models. It is very difficult to predefine a color model in a mobile application where the light condition may change dramatically over time. In this paper, we propose a novel statistical approach to hand segmentation based on Bayes decision theory. The proposed method requires no predefined skin color model. Instead it generates a hand color model and a background color model for a given image, and uses these models to classify each pixel in the image as either a hand pixel or a background pixel. Models are generated using a Gaussian mixture model with the restricted EM algorithm. Our method is capable of segmenting hands of arbitrary color in a complex scene. It performs well even when there is a significant overlap between hand and background colors, or when the user wears gloves. We show that the Bayes decision method is superior to a commonly used method by comparing their upp...

• Type: Conference
• Year: 2000
• Where: FGR
• Authors: Xiaojin Zhu, Jie Yang, Alex Waibel
• Keywords: Biometrics, Color Model, FGR 2000, Predefined Skin Color, Skin Color Model