Department of Electrical & Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA ; Biometrics Research Center, Department of Computing, The Hong Kong Polytechnic University, Hong Kong.
Evid Based Complement Alternat Med. 2013;2013:264742. doi: 10.1155/2013/264742. Epub 2013 Apr 22.
An in-depth systematic tongue color analysis system for medical applications is proposed. Using the tongue color gamut, tongue foreground pixels are first extracted and assigned to one of 12 colors representing this gamut. The ratio of each color for the entire image is calculated and forms a tongue color feature vector. Experimenting on a large dataset consisting of 143 Healthy and 902 Disease (13 groups of more than 10 samples and one miscellaneous group), a given tongue sample can be classified into one of these two classes with an average accuracy of 91.99%. Further testing showed that Disease samples can be split into three clusters, and within each cluster most if not all the illnesses are distinguished from one another. In total 11 illnesses have a classification rate greater than 70%. This demonstrates a relationship between the state of the human body and its tongue color.
提出了一种用于医学应用的深入系统的舌色分析系统。使用舌色域,首先提取舌前景像素,并将其分配给表示该色域的 12 种颜色之一。计算整个图像的每种颜色的比例,并形成舌色特征向量。在包含 143 个健康样本和 902 个疾病样本(13 组超过 10 个样本和一个杂项组)的大型数据集上进行实验,给定的舌样本可以分为这两类中的一类,平均准确率为 91.99%。进一步的测试表明,疾病样本可以分为三个聚类,并且在每个聚类中,大多数(如果不是全部)疾病彼此之间都可以区分开来。共有 11 种疾病的分类率大于 70%。这表明人体的状态与其舌色之间存在关系。