Tongue Diagnosis System Based on PCA and SVM

Authors: Jin-Woong Park, Sun-Kyung Kang, Sung-Tae Jung

Abstract:

In this study, we propose a tongue diagnosis method which detects the tongue from face image and divides the tongue area into six areas, and finally generates tongue coating ratio of each area. To detect the tongue area from face image, we use ASM as one of the active shape models. Detected tongue area is divided into six areas widely used in the Korean traditional medicine and the distribution of tongue coating of the six areas is examined by SVM(Support Vector Machine). For SVM, we use a 3-dimensional vector calculated by PCA(Principal Component Analysis) from a 12-dimentional vector consisting of RGB, HIS, Lab, and Luv. As a result, we detected the tongue area stably using ASM and found that PCA and SVM helped raise the ratio of tongue coating detection.

Keywords: Active Shape Model, Principal Component Analysis, Support Vector Machine, Tongue diagnosis

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1062204

References:

[1] C.-C. Chiu, "A novel approach based on computerized image analysis for traditional Chinese medical diagnosis of the tongue," Computer Methods and Programs in Biomedicine, vol. 61, pp. 77-89, 2000.
[2] Stephen Milborrow, Fred Nicolls, "Locating Facial Features with an Extended Active Shape Model," Lecture notes in computer science,2008
[3] Su-Joong Kim, Jae-Keun Hong, "A Simplification of Polynomial Representations for the Moments of the Mahalanobis Distances," Journal of the Korean Institute of Electronics Engine- ers, vol.21 no.3, pp. 1~5, May, 1984
[4] V.Vapnik, The Nature of Statistical Learning Theory, Springer-verlag, New York, 1995.
[5] CJC. Burges, " A Tutorial on Support Vector Machines for Pattern Recognition," In Data Mining and Knowledge Discovery, Vol.2 No. 2, pp. 121-167, 1998.
[6] H.Z. Zhang; K.Q. Wang; D. Zhang; B. Pang; B. Huang, "Computer Aided Tongue Diagnosis System," Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the Digital Object Identifier pp. 6754 - 6757, Setember, 2005
[7] Keun-Ho Kim, Jun-Hyeong Do, Hyun-Hee Ry- u, Kim, Jong-Yeol, "Systematic Approach to The Extraction of Effective Region for Tongue Diagnosis," Journal of the Institute of Electro- nics Engineers of Korea. SC, System and control, v.45 no.6, pp. 123-131, Nov. 2008
[8] Hao Zhu, Wangmeng Zuo, Hongzhi Zhang, Jianfeng Li, David Zhang, "Exploratory Tongue Color Analysis with Manifold Learning," Biomedical Engineering and Informatics, pp. 244-248, October, 2010