Tongue diagnosis method for extraction of effective region and classification of tongue coating
Tongue diagnosis method for extraction of effective region and classification of tongue coating
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DOI：
10.1109/ipta.2008.4743772
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发表时间：
2008-11
期刊：
影响因子：
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通讯作者：
K. Kim;Jun-Hyeong Do;H. Ryu;J.-Y. Kim
中科院分区：
文献类型：
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作者：
K. Kim;Jun-Hyeong Do;H. Ryu;J.-Y. Kim
在东方医学中，舌的状态与人体内部的生理和临床病理变化一样，是诊断一个人健康状况的重要指标。舌诊不仅方便而且无创，在东方医学中应用广泛。然而，舌诊受检查环境的影响，如光源，患者的姿势和医生的条件。为了开发用于客观和标准化诊断的自动舌诊系统，从所捕获的面部图像分割舌头并对舌苔进行分类是不可避免的，但由于舌头、嘴唇和口腔中的皮肤的颜色相似，因此是困难的。所提出的方法包括预处理、过分割、检测具有局部最小值超过来自舌头结构的阴影的位置、校正局部最小值或检测具有色差的边缘以及平滑边缘，其中预处理执行下采样以减少计算时间、直方图均衡化和边缘增强，这产生分割的舌头的区域，然后将该区域的颜色分量分解为色调、饱和度和亮度，从而分割出舌苔区域并进行分类。最后，从人脸图像中分割出舌体，并将舌体分类为舌苔和舌苔物质。实验结果表明，分割后的区域包含了有效信息，排除了非舌区域，能够准确诊断舌苔。它可以用于做出客观和标准化的诊断。
In oriental medicine, the status of a tongue is the important indicator to diagnose one's health like physiological and clinicopathological changes of inner parts of the body. The method of a tongue diagnosis is not only convenient but also non-invasive and widely used in oriental medicine. However, a tongue diagnosis is affected by examination circumstances a lot like a light source, patient's posture, and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue from a facial image captured and classifying tongue coating are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth are similar. The proposed method includes preprocessing, over-segmentation, detecting positions with a local minimum over shading from the structure of a tongue, correcting local minima or detecting edge with color difference, and smoothing edges, where preprocessing performs downsampling to reduce computation time, histogram equalization, and edge enhancement, which produces the region of a segmented tongue, and then decomposes the color components of the region into hue, saturation and brightness, resulting in segmenting the regions of tongue coatings and classifying them. Finally, a tongue is segmented from a face image and classified into kinds of coatings and substance with a tongue from a digital tongue diagnosis system. The results illustrate the segmented region to include effective information, excluding a non-tongue region and the accurate diagnosis of coatings. It can be used to make an objective and standardized diagnosis.