the classification of tongue colors with standardized acquisition and icc profile correction in traditional chinese medicine

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ID: 244624
2016
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Abstract
Background and Goal. The application of digital image processing techniques and machine learning methods in tongue image classification in Traditional Chinese Medicine (TCM) has been widely studied nowadays. However, it is difficult for the outcomes to generalize because of lack of color reproducibility and image standardization. Our study aims at the exploration of tongue colors classification with a standardized tongue image acquisition process and color correction. Methods. Three traditional Chinese medical experts are chosen to identify the selected tongue pictures taken by the TDA-1 tongue imaging device in TIFF format through ICC profile correction. Then we compare the mean value of L*a*b* of different tongue colors and evaluate the effect of the tongue color classification by machine learning methods. Results. The L*a*b* values of the five tongue colors are statistically different. Random forest method has a better performance than SVM in classification. SMOTE algorithm can increase classification accuracy by solving the imbalance of the varied color samples. Conclusions. At the premise of standardized tongue acquisition and color reproduction, preliminary objectification of tongue color classification in Traditional Chinese Medicine (TCM) is feasible.
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qi2016biomedthe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Zhen Qi;Li-ping Tu;Jing-bo Chen;Xiao-juan Hu;Jia-tuo Xu;Zhi-feng Zhang
Journal spectrochimica acta - part a: molecular and biomolecular spectroscopy
Year 2016
DOI
10.1155/2016/3510807
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