Evaluation of Art Works Based on Expert System and Improved Image Algorithm

In order to improve the quality of digital evaluation of works of art, this paper combines an expert system and an improved image algorithm to build an evaluation model of works of art, realizes rapid analysis of works of art through the intelligent model, puts forward some image features for classification of works of art, and uses multi-core learning to classify images of works of art. The purpose of this paper is to provide some objective criteria for experts by using image classification technology and to assist experts in art works to identify the text information such as the origin, theme, and age of art works more accurately. In order to extract coloring style information of works of art, we measure the number of colors in an image by color saturation and then extract style information by analyzing the color distribution of a colored area. The research results of this paper show that the evaluation system of art works based on expert system and improved image algorithm can effectively improve the digital processing effect of art works and enhance the intelligent evaluation efficiency of art works.