Classification of lip color based on multiple SVM-RFE

Classification of lip color is an important aspect in the theory of Traditional Chinese Medicine (TCM). The lip color of one person can reflect the person's healthy status. This paper investigates the effectiveness of multiple support vector machine recursive feature elimination (SVM-RFE) for feature selection in the classification of lip color. In the proposed method, both the normalized histogram features and the mean/variance features are computed for the ranking score from a statistical analysis of weight vectors of multiple linear SVMs trained on subsamples of the original training data. Experimental results show that not only the multiple SVM-RFE is effective for feature selection in the lip color classification, but also the accuracy rate of classification of the proposed method is better than the existing SVM method, which is close up to 91%.