皮肤颜色是人脸检测、定位、跟踪时的一种十分有效的特征,而且裸露的皮肤区域也是色情图像的最重要特征之一.为了有效地进行图像的皮肤检测,提出了一种新的肤色检测方法.该方法首先通过统计1809 502个肤色像素点和1763682个非肤色像素点,并使用贝叶斯规则来建立肤色分类器;然后考虑亮度对肤色的影响,采用Y-Cb和Y-Cr两个子空间的查询表来建立肤色模型.为了联合使用两个查询表,先采用高斯归一化和线性化方法来将阈值范围调整至[0,1];同时对查询表进行中值滤波处理,以除去离散孤立点.实验表明,与其他3种方法相比,该方法不仅有着较低的漏检率（9.814%）和误检率（3.5%）,而且对于不同光照条件也有较好的检测效果.

Skin color has been proven to be a useful and robust cue for face detection,localization and tracking.Naked skin region is one of the most important features to detect the erotic pictures.For detecting the skin images effectively,a skin color classification technique that employs Bayesian decision with color statistics data,which include(1 809 502) skin pixels and(1 763 682) non-skin pixels gathered from YCbCr color space,has been presented.Considering the influence of luminance(Y component) on skin color,the skin color model is constructed by two lookup tables in Y-Cb and Y-Cr subspaces.To use 2 lookup tables(LUTs) together,Gaussian normalization and linear converting are used to normalize the range of threshold value to.To filter scattering points,both LUTs are processed by median filter.Experimental results have demonstrated that this method can provide lower false dismissal rate(9.814%) lower false detection rate(3.5%),compared with three methods given in this paper,and achieve better detection performance in various lighting conditions.