PLS and LDA for Gloss Recognition in Facial Inspection of Traditional Chinese Medicine
基于PLS、LDA 的中医面诊光泽识别研究

The study was aimed to explore objective recognition method for gloss of facial complexion in traditional Chinese medicine (TCM). Computer vision skills were utilized and feature extraction methods, such as PLS, LDA and 2DLDA, were applied to face samples in 13 color spaces as facial gloss extraction methods. The results showed that PLS, LDA, 2DLDA in RGB, HSV, Lab color space of these three channels were higher than on which is right to judge the results of single-channel. Feature extraction methods in different color channels are different from the correct rate. PLS may reach to the rate of 89.06% in the Lab color space. LDA may reach to the rate of 88.69% in the Lab color space. The 2DLDA may reach to the rate of 89.00% in the RGB color space. It is concluded that these three methods have a positive effect on gloss information extraction. It provides a new method for TCM observation of gloss quantification examination.