Semi-supervised classification on "warm or cool" color in tongue images

Bo Huang, Dapeng Zhang, Hongzhi Zhang, Yanlai Li, Naimin Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Examination of the tongue condition is a standard diagnostic method in Traditional Chinese Medicine (TCM) and takes account of a wide variety of features including shape, texture, and color. The terms "warm", "neutral", and "cool" are used to refer to a kind of chromatics characteristic of the tongue color and are associated with various health states. In this paper, we propose a semi-supervised (cluster and label) scheme for tongue color analysis on "warm or cool". In the training part, the proposed scheme makes use of a classical clustering algorithm, Expectation Maximization, to divide all pixels in tongue gamut into 150 clusters. Then we construct two auxiliary images for each cluster and manual labeling endows these clusters with category labels of "warm or cool". Finally, each trained category on "warm or cool" is set up by sum some clusters approximately. In the testing part, we use a lookup table to divide all pixels in an input image into three distinct categories of "warm or cool". In experiments conducted on a total of 392 tongue samples, our system achieved an accuracy of 91.1%.
Original languageEnglish
Title of host publication2011 3rd International Conference on Advanced Computer Control, ICACC 2011
Number of pages4
Publication statusPublished - 4 Oct 2011
Event3rd IEEE International Conference on Advanced Computer Control, ICACC 2011 - Harbin, China
Duration: 18 Jan 201120 Jan 2011


Conference3rd IEEE International Conference on Advanced Computer Control, ICACC 2011


  • Computerized tongue diagnosis
  • semi supervised learning
  • warm or cool

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering

Cite this