中文摘要：

目的观察常用色彩空间哪个通道（或分量）善于反映舌质舌苔的区别并有助于舌质舌苔的分割。方法以典型舌图（淡红舌薄白苔、腻苔、黄苔等）和色温偏低的舌图为研究对象,在红、绿、蓝三色（RGB）,国际照明委员会1976 L^＊a^＊b^＊标准（CIELAB）和色调、饱和度、亮度（HSI）色彩空间下选择舌图上每个像素的特定色彩分量（a^＊分量、L^＊分量、H分量、R分量）作为聚类对象。使用K-均值聚类聚成2个集合,按照生成的2个集合的特征完成分割。结果显示CIELAB色彩空间a^＊分量对舌质舌苔分割的效果和抗干扰能力最好,不受光照角度、色温偏差、舌苔舌质类型等因素的影响。L^＊分量、R分量的聚类结果受光照不均匀的影响明显,H分量的聚类结果多呈分割不完全状态。结论基于K-均值聚类的以CIELAB色彩空间a^＊分量为指标对舌质舌苔进行分割的效果较稳定,在舌诊中有一定的实用价值。

英文摘要：

Objective To observe which pathways （or components） of common color spaces are good for discriminating and segmenting tongue body and fur. Methods The typical tongue image （pink tongue with thin-white fur, greasy fur and yellow fur） and lower color temperature tongue image were taken as study objects, and special color component of every pixel of tongue imagines （value of a ＊ , L ＊ , H and R） in the color spaces of red, green and blue （ RGB）, L ＊ a ＊ b ＊ criterion of International Commission on Illumination in 1976 （CIELAB）, and hue, saturation and intensity （HSI） were selected as clustering objects. K-means clustering was applied to generate two clusters and complete the segmentation according to the characteristics of them. Results The component of a＊ value of CIELAB color space was the best in the segment effect and anti-interference capability, which was not influenced by illumination angle, bias of color temperature and types of tongue body and fur. The clustering results of L＊ value and R value were influenced by uneven illumination significantly. The clustering result of H value showed a state of incomplete segmentation. Conclusion The segmentation of tongue body and fur had a stable result taking a＊ value in CIELAB color space based K-means clustering as index and showed practical values in tongue diagnosis.