基于局部马尔科夫随机场的模型校准嘴唇分割方法

A Local MRF Model Based Lip Segmentation Method with Model Calibration

  • 摘要: 为了有效挖掘人说话时的唇动特征,提出了一种综合局部区域马尔科夫随机场(Markov random field,MRF)特性和模型校准的嘴唇分割方法。将嘴唇区域图像从RGB转换到LUX色彩空间,并利用对数化色彩分量U实现初始化轮廓的确定。沿轮廓选取固定半径的圆形窗口函数界定局部区域,再利用马尔科夫随机场进行嘴唇分割,并使用基于Kullback-Leiller(KL)距离的模型校准方法使局部区域之间的分割结果相互协调。实验证明,该方法可以在皮肤中分离出嘴唇,分割准确率高,鲁棒性好,具有较高的实用价值。

     

    Abstract: In order to effectively exploit the lip feature of human speech, a lip segmentation method based on Markov random field (MRF) and model calibration is proposed. In this paper, we conduct the color space transformation from RGB to LUX color space for the lip region image, and we make use of the logarithmic chroma U to determine the initial contour. A mask with fixed radius is selected along the contour to define the local region, the Markov random field is used to segment the lips, and the Kullback-Leiller (KL) distance based model calibration method is used to coordinate the segmentation results between the local regions. Experiments show that the method can separate the lips in the skin with high accuracy and robustness and is of high practical value.

     

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