Abstract:Skin detection is an important preprocessing step of numerous image
processing applications. Almost all the arithmetics address this
issue pixel by pixel only allowing for the color information but
humans do not. In this paper, a novel approach is proposed for skin
detection, which takes use of both color information and region
information. Meanwhile, taking into consideration the weakness of
the statistical model, we do some post processing on the binary
result to improve the skin detection effect. In the experiment, we
firstly establish a histogram model based on training dataset. And
then do the detection on the test dataset based on the renowned
Compaq dataset which was widely used. Finally some special images
are also selected to verify the effectiveness of our approach. And
the experimental results also demonstrate that our proposed method
is superior than the state of art arithmetics.
Jiang Xue;Zhiyan Wang. An Improved Statistic Model in Skin Detection[J]. , 2014, 11(11): 3643-3651.
Jiang Xue;Zhiyan Wang. An Improved Statistic Model in Skin Detection. , 2014, 11(11): 3643-3651.