Novel Binary Classification Method for Traditional Chinese Paintings and Caligraphy Images
一种传统中国书画图像的二分类方法

Traditional chinese painting(TCP) and calligraphy is unique forms of art.With the rapid development of digi-tal technology,more and more TCP and Calligraphy works are digitized.How to effectively retrieve these images becomes a hot topic.If we first classify the TCP and Calligraphy images,this will be a solid foundation for retrievaling those images.We proposed an improved classification method of those images.’Liubai’ area was detected firstly,and removed it from the images,because these regions contain noise information which will make the classifation results inaccurate.The second step was to extract feature from those images.At last,the features were used to training the Support Vector Machine(SVM) model.And the trained model was used to classifying the TCP and Calligraphy images.The classification result shows this method has better effect.