ArticleBioMed research international2014
Qualitative and quantitative analysis for facial complexion in traditional Chinese medicine.
Article in BioMed research international, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 31 citations in OpenAlex.
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- Deep learning approach for objective differentiation of kidney deficiency syndrome in reproductive age females: a tongue-face fusion model.Frontiers in physiology · 2025Article
- Noncontact evaluation of autonomic nervous system activity during exercise by using video analysis.Frontiers in digital health · 2025Article
- The Relationship Between Computerized Face and Tongue Image Segmentation and Metabolic Parameters in Patients with Type 2 Diabetes Based on Machine Learning.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Article
- A research on syndrome element differentiation based on phenomenology and mathematical method.Chinese medicine · 2017Article
- The Association of Quantitative Facial Color Features with Cold Pattern in Traditional East Asian Medicine.Evidence-based complementary and alternative medicine : eCAM · 2017Article
- Big data is essential for further development of integrative medicine.Chinese journal of integrative medicine · 2015Article
- Yang Deficiency Body Constitution Acts as a Predictor of Diabetic Retinopathy in Patients with Type 2 Diabetes: Taichung Diabetic Body Constitution Study.Evidence-based complementary and alternative medicine : eCAM · 2015Article
- Development and Preliminary Validation of the Questionnaire (the First Edition) Based on TCM for Detecting Health Status in China.Evidence-based complementary and alternative medicine : eCAM · 2015Article
- Advances in Patient Classification for Traditional Chinese Medicine: A Machine Learning Perspective.Evidence-based complementary and alternative medicine : eCAM · 2015Review
- A new method for assessing chronic insomnia: Machine learning-based fusion of TCM observation digital features.Digital healthArticle
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Authors and funding
5 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Facial diagnosis is an important and very intuitive diagnostic method in Traditional Chinese Medicine (TCM). However, due to its qualitative and experience-based subjective property, traditional facial diagnosis has a certain limitation in clinical medicine. The computerized inspection method provides classification models to recognize facial complexion (including color and gloss). However, the previous works only study the classification problems of facial complexion, which is considered as qualitative analysis in our perspective. For quantitative analysis expectation, the severity or degree of facial complexion has not been reported yet. This paper aims to make both qualitative and quantitative analysis for facial complexion. We propose a novel feature representation of facial complexion from the whole face of patients. The features are established with four chromaticity bases splitting up by luminance distribution on CIELAB color space. Chromaticity bases are constructed from facial dominant color using two-level clustering; the optimal luminance distribution is simply implemented with experimental comparisons. The features are proved to be more distinctive than the previous facial complexion feature representation. Complexion recognition proceeds by training an SVM classifier with the optimal model parameters. In addition, further improved features are more developed by the weighted fusion of five local regions. Extensive experimental results show that the proposed features achieve highest facial color recognition performance with a total accuracy of 86.89%. And, furthermore, the proposed recognition framework could analyze both color and gloss degrees of facial complexion by learning a ranking function.
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