Abstract:In recent years, the rapid progress of nondestructive diagnosis of scar has been achieved by computer technology, and the quantitative analysis of scar image texture has been well diagnosed. In this process there have been many texture description methods, the proposed method also contributed to the development of texture research. In this paper, we introduce the experimental results of different methods on the scar image by using the gradient iterative regression tree algorithm, and get the regression model of different methods in the case of gray level cooccurrence matrix(GLCM) and local ternary pattern(LTP) statistical analysis methods. The performance of these models is reflected in the ability to predict the scars of different ages. The local difference local binary pattern (LDLBP) operator and the local orientation ternary pattern(LOTP) operator have the best predictors of the model, which shows that they are one of the most accurate methods for describing the texture of scar images. The statistical texture analysis method is suitable for the texture study of scar images.