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首页> 外文期刊>Chinese Journal of Electronics >Fuzzy Support Vector Machine Based on Color Modeling for Facial Complexion Recognition in Traditional Chinese Medicine
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Fuzzy Support Vector Machine Based on Color Modeling for Facial Complexion Recognition in Traditional Chinese Medicine

机译：基于颜色建模的模糊支持向量机在中医面部肤色识别中的应用

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摘要

Face diagnosis is one of the four diagnostic methods in Traditional chinese medicine (TCM). The morbidity of the organs can be revealed from the facial complexion. Due to the ambiguity of face diagnosis in TCM, Fuzzy support vector machine (FSVM) is utilized to remove the influence of outliers. The facial complexion recognition in TCM based on FSVM is proposed in this paper, which includes the following steps: 1) The facial cheek region are segmented as skin blocks; 2) The color feature in Lab color space is extracted from skin block to represent facial complexion characteristic; 3) The fuzzy membership is calculated to obtain the membership of the training samples, in which the final membership of training samples is determined by combining membership calculation based on distance with the facial complexion recognition based on color modeling; 4) The FSVM is built to classify facial complexion characteristic. Experimental results show that proposed facial complexion recognition has better anti-interference performance as well as a higher recognition rate up to 82%.
机译：面部诊断是中医（TCM）的四种诊断方法之一。可以从面部肤色中看出器官的发病率。由于中医中人脸诊断的含糊不清，因此利用模糊支持向量机（FSVM）来消除离群值的影响。提出了基于FSVM的中医面部肤色识别方法，包括以下步骤：1）将脸颊区域分割为皮肤块； 2）从肤色块中提取Lab色彩空间中的色彩特征，以表示面部肤色特征； 3）计算模糊隶属度，得到训练样本的隶属度，将基于距离的隶属度计算与基于颜色建模的面部肤色识别相结合，确定训练样本的最终隶属度； 4）建立FSVM可以对面部肤色特征进行分类。实验结果表明，提出的面部肤色识别具有较好的抗干扰性能，识别率高达82％。

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