Title :
Classification of tongue coating using Gabor and Tamura features on unbalanced data set
Author :
Xiaoqiang Li ; Qing Shao ; Jingjing Wang
Author_Institution :
Sch. of Comput. Eng. & Sci., Shanghai Univ., Shanghai, China
Abstract :
Rotten and greasy coating on tongue is one of the most salient features reflecting inner health of body, which is widely used in observe diagnosis in Traditional Chinese Medicine (TCM). This paper is mainly concentrated on the classification of two tongue coating states: rotten and greasy. As it is an unbalanced classification and texture recognition problem, method of random oversampling, Gabor feature and distribution feature of tongue coating will be used in our algorithm framework.
Keywords :
Gabor filters; bioinformatics; feature extraction; image classification; image texture; medical image processing; Gabor feature; Tamura feature; algorithm framework; distribution feature; greasy coating; random oversampling method; rotten coating; texture recognition; tongue coating classification; traditional Chinese medicine; unbalanced data set; Accuracy; Coatings; Feature extraction; Manganese; Support vector machines; Tongue; Training; Gabor feature; TCM; balanced treatment; classification of coating;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
Conference_Location :
Shanghai
DOI :
10.1109/BIBM.2013.6732649
