Study on complexion recognition in TCM

Author

Tunhua, Wu ; Baogang, Bai ; Fushun, Sun ; Changle, Zhou ; Ping, Wang

Author_Institution

Sch. of Inf. & Eng., Wenzhou Med. Coll., Wenzhou, China

Volume

3

fYear

2010

fDate

12-13 June 2010

Firstpage

487

Lastpage

490

Abstract

Based on complexion-viscera diagram in TCM (Traditional Chinese Medicine), a method for complexion recognition was proposed for the first time. Firstly, the sampling environment was standardized, and 68 common facial feature points were localized by AdaBoost and ASM algorithm. Second, the complexion features in LAB color space were extracted from 15 diagnostic feature points on complexion-viscera diagram by FCM clustering which separates the complexion feature from skin color. Finally, the complexion features were classified by SVM algorithm. This method can be applied to the automatic logic inference of face diagnosis in TCM. Experiments on a test set of 400 face images result an accuracy of 84.6%. Results prove the effectiveness and efficiency of this method.

Keywords

face recognition; feature extraction; image colour analysis; inference mechanisms; learning (artificial intelligence); pattern clustering; sampling methods; support vector machines; ASM algorithm; AdaBoost algorithm; FCM clustering; LAB color space; SVM algorithm; active shape model; automatic logic inference; complexion recognition; complexion-viscera diagram; facial feature points; feature extraction; fuzzy c-means; sampling environment; support vector machines; traditional Chinese medicine; Educational institutions; Support vector machines; ASM; AdaBoost; FCM; SVM; TCM;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Communication Technologies in Agriculture Engineering (CCTAE), 2010 International Conference On

Conference_Location

Chengdu

Print_ISBN

978-1-4244-6944-4

Type

conf

DOI

10.1109/CCTAE.2010.5544338

Filename

5544338