Classification of Landscape Painting Texturing Based on Gabor

Extracting the effective features for texture description and classification has always been the hot spot of the texture analysis. In this paper, according to different texture of traditional Chinese painting, we use a kind of Gabor filter technique to classify the painting. By texture feature extraction, first of all, we preprocess the traditional Chinese painting images with geometric normalization and light normalization, after that we process the group of the Gabor filter of high dimensional feature vectors by principal component analysis (PCA) for dimension reduction. Finally, support vector machine (SVM) method is employed for texture classification. The accuracy rate of this classification method can reach 95.5%.