C2G2FSnake: automatic tongue image segmentation utilizing prior knowledge
C2G2FSnake: automatic tongue image segmentation utilizing prior knowledge
复制标题
C2G2FSnake：利用先验知识自动舌头图像分割
DOI：
10.1007/s11432-011-4428-z
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发表时间：
2013-09-01
影响因子：
8.8
通讯作者：
Li FuFeng
中科院分区：
文献类型：
--
作者：
Shi MiaoJing;Li GuoZheng;Li FuFeng
从数字图像中提取舌体是中医舌诊自动化的关键。本文提出了一种全自动的主动轮廓初始化方法，利用先验知识的舌头形状和它在舌图像中的位置。然后引入颜色空间信息来控制曲线的演化。结合几何Snake模型和参数化GVFSnake模型，提出了一种新的舌体自动分割方法：C2 G2 FSnake（color control-geometric & gradient flow Snake）。该方法提高了曲线的速度，但降低了复杂度。C2 G2 FSnake极大地扩展了舌体分割的实际应用，同时提高了精度。与现有的基于不同舌色图像的舌体分割方法相比，C2 G2 FSnake实现了舌体的自动分割，准确率有了很大的提高。
Extraction of the tongue body from digital images is essential for automated tongue diagnoses in traditional Chinese medicine. This paper presents a fully automated active contour initial method that utilizes prior knowledge of the tongue shape and its location in tongue images. Then colorspace information is introduced to control curve evolution. Combining the geometrical Snake model with the parameterized GVFSnake model, a novel approach for automatic tongue segmentation: C2G2FSnake (color control-geometric & gradient flow Snake) is proposed. This method increases the curve velocity but decreases the complexity. C2G2FSnake greatly extends practical usage to tongue segmentation, at the same time increasing the precision. Compared with other state-of-the-art works using different images of tongue color, C2G2FSnake realizes automatic tongue segmentation with greatly improved accuracy.