Analysis of Painting Complexity Based on Feature Extraction

As an important part of art, painting reflects the development of human culture and thoughts. The purpose of this work was to investigate the features that could affect the complexity of the artworks. The features of the artworks were classified into three categories: stroke feature, color features and texture features. The famous artist – Picasso’s paintings were used as examples. In the end, two models for predicting complexity were proposed and we found that stroke feature was the most significant. The results from the overall research enabled us to quantify the image complexity based on the features, thus, it is helpful to grasp the difficulty of image processing or to measure the aesthetic value of the picture.