Feature Extraction and Analysis for Scientific Understanding of Visual Art

Yi Zhang, Yuanyuan Pu, Yaqun Huang, Dan Xu, Wenhua Qian

Abstract: In this paper, the research of visual art based on the computer and information of paintings, which can be called scientific understanding of visual art, has been brought out. Four features, multi-scale amplitude, non-stationarity of artworks, anisotropy of artworks and correlation of coefficients of the curve let transform between scales, are extracted based on the curve let transform to evaluate the style of different artists. The relations between the style of visual art and these features are also stated, and the similarities of these styles are also qualified by comparing these features. It is apparent that each feature reflects different characteristics of the different school paintings.