基于支持度变换的水平集人脸轮廓提取方法

A Level Set Method for Facial Contour Extraction Based on Support Value Transform

提出了一种新的人脸轮廓提取方法,该方法将水平集与支持度相结合.首先将人脸图像进行支持度变换得到支持度图像,在此基础上,用支持度图像计算几何活动轮廓模型的边缘指示函数,在演化过程中先选取参数较小的边缘指示函数,使得边缘指示函数对眉毛不敏感,演化曲线过眉毛后选取参数较大的边缘指示函数,使得演化正确收敛于人脸轮廓.实验结果表明该方法的人脸轮廓提取效果较好,收敛速度快.

A novel facial contour extraction method is proposed, which combines the level set method and the support vector transform. The support value image is obtained by using support value transform. Then the level set method uses the support value image to compute the edge indicator. In order to avoid the effect of the eyebrow, the small parameter of edge indicator function first is used. After the evolving curve evolved across the eyebrow, the large parameter of edge indicator function is chosen. Then the evolving curve stops when it arrives to the facial contour. The experimental results show that the proposed method has advantages over the direct geometric active contours in converging speed and facial contour extraction accuracy.