Tongue Diagnosis Based on Biometric Pattern Recognition Technology

Wang, K.; Zhang, D.; Li, N.; Pang, Bo

doi:10.1142/9789812386533_0021

Cited by 14 publications

(12 citation statements)

References 0 publications

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“…Diseases 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, and 13 achieved an average accuracy greater than 70% and therefore deemed successfully classified. Typical samples of the successfully classified illnesses are shown in Figures 12,13,14,15,16,17,18,19,20, 21, and 22.…”

Section: Typical Disease Analysismentioning

confidence: 99%

“…The patients were also diagnosed using Chinese Medicine. As for [13] its dataset was substantially larger but only appendicitis was classified. The samples in [14] include two illnesses as well as normal, but their sizes are too small to have any statistical significance.…”

Section: Introductionmentioning

confidence: 99%

“…Both works in Miscellaneous 500 [12,14] did not use any image correction to ensure uniform feature extraction and analysis under different operating conditions. Also, [12][13][14] used some variation of the CIE color space to embody the tongue colors, which may not be very accurate. Therefore, there is a lack of any work on an indepth systematic tongue color analysis system for medical applications, one that accurately captures the images and represents its colors using a tongue color gamut [15].…”

Section: Introductionmentioning

confidence: 99%

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Tongue Color Analysis for Medical Application

Zhang

2017

Tongue Image Analysis

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An in-depth systematic tongue color analysis system for medical applications is proposed. Using the tongue color gamut, tongue foreground pixels are first extracted and assigned to one of 12 colors representing this gamut. The ratio of each color for the entire image is calculated and forms a tongue color feature vector. Experimenting on a large dataset consisting of 143 Healthy and 902 Disease (13 groups of more than 10 samples and one miscellaneous group), a given tongue sample can be classified into one of these two classes with an average accuracy of 91.99%. Further testing showed that Disease samples can be split into three clusters, and within each cluster most if not all the illnesses are distinguished from one another. In total 11 illnesses have a classification rate greater than 70%. This demonstrates a relationship between the state of the human body and its tongue color.

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Section: Typical Disease Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Tongue Color Analysis for Medical Application

Zhang

2017

Tongue Image Analysis

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“…Wang, Zhang, & Li, 2001). These images are captured by traditional charge coupled device (CCD) cameras which can only provide the spatial and colour information of tongue surface.…”

Section: Hyperspectral Tongue Imaging Systemmentioning

confidence: 99%

Hyperspectral Imaging Technology Used in Tongue Diagnosis

Li¹

2012

Recent Advances in Theories and Practice of Chinese Medicine

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“…Nowadays, the rapid progress of information technology promotes the automatization of tongue disease diagnosis based on modern image processing and pattern recognition approaches [7,8]. For example, Li and Yuen [9] investigated the color matching of tongue images in different color spaces with different metrics.…”

Section: Introductionmentioning

confidence: 99%