Complexity perception classification method for tongue constitution recognition
Complexity perception classification method for tongue constitution recognition
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DOI：
10.1016/j.artmed.2019.03.008
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发表时间：
2019-05-01
影响因子：
7.5
通讯作者：
Jiang, Lijun
中科院分区：
文献类型：
--
作者：
Ma, Jiajiong;Wen, Guihua;Jiang, Lijun
人体体质与疾病及相应的中医治疗方案有着密切的关系。它可以通过舌象诊断来识别，因此它本质上被视为舌象分类问题，其中每个舌象都被分为九种构成类型中的一种。本文首先提出了一个通过自然舌头图像自动识别舌头结构的系统框架，其中精心设计了深度卷积神经网络用于舌苔检测、舌苔校正和舌头结构识别。在该系统框架下，提出了一种新的复杂性感知（CP）分类方法，较好地处理了环境条件变化和舌头图像分布不均匀对结构识别性能的不良影响。CP根据单个舌图像的复杂程度，选择具有相应复杂程度的分类器进行构造识别。为了评估该方法的性能，在医院的三种尺寸的临床舌图像上进行了实验。实验结果表明，该方法能有效提高人体体质识别的准确率。
The body constitution is much related to the diseases and the corresponding treatment programs in Traditional Chinese Medicine. It can be recognized by the tongue image diagnosis, so that it is essentially regarded as a problem of tongue image classification, where each tongue image is classified into one of nine constitution types. This paper first presents a system framework to automatically identify the constitution through natural tongue images, where deep convolutional neural networks are carefully designed for tongue coating detection, tongue coating calibration, and constitution recognition. Under the system framework, a novel complexity perception (CP) classification method is proposed to nicely perform the constitution recognition, which can better deal with the bad influence of the variation of environmental condition and the uneven distribution of the tongue images on constitution recognition performance. CP performs the constitution recognition based on the complexity of individual tongue images by selecting the classifier with the corresponding complexity. To evaluate the performance of the proposed method, experiments are conducted on three sizes of clinic tongue images from hospitals. The experimental results illustrate that CP is effective to improve the accuracy of body constitution recognition.