Oil Painting Art Style Extraction Method Based on Image Data Recognition

This paper introduces the background and significance of oil painting art style research and summarizes the concept and development of oil painting. Based on the research of image data recognition technology, a new method of oil painting art style extraction based on image data recognition is proposed. The visual features of oil painting images in hue, lightness, and purity are calculated in color space, which are divided into global color features and local color features. Color image boundaries are obtained by using structures of various scales, and then the boundaries are synthesized by multiscale merging algorithm to obtain the boundary results. Using a module fixing and dividing method, we can get the local area that can best show the characteristics of the writer’s painting style. The oil paintings are described by the key region algorithm, and then their artistic style features are obtained. Experiments show that this method is effective and reliable, and the recognition rate of this algorithm is higher than that of other algorithms. This study not only solves the problem that the selection of local areas is too subjective, but also provides new ideas for the study of oil paintings.