Application of Line Integral Convolution Techniques in the Generation of Fine Art Painting Effects

Abstract

Since the 1980s, nonrealistic drawing techniques have become one of the main focuses of research in computer graphics. In recent years, with the rapid development of computer graphics, nonrealistic drawing techniques have become capable of rendering any digital image into an image with an alternative artistic style. As a result, many scholars have focused on the pencil sketch style. Against this backdrop, research into how to create more realistic art drawings has become a hot topic. Although the rapid development of computer technology has led to advances in art drawing techniques, traditional fine art painting methods are not yet able to simulate realistic pencil sketches in a quite realistic way. In other words, the following issues have been noted. For example, they fail to simulate the gradation of shades and densities of real sketches, the direction of the shadows does not conform to the general rules of sketching, and the results produced are not artistic and realistic. After all, unlike realistic graphics, which seeks a photo-like realism, nonrealistic graphics wants to highlight the message of the image with the help of computer simulations. As a result, nonrealistic graphics often ignores unimportant details in the image. On the other hand, nonrealistic graphics can also simulate an artist’s painting to a certain extent, thus producing an artistically effective image. Many nonrealistic drawing methods have been devised to simulate the styles of oil, watercolour, and ink, but not many algorithms have been developed to generate colour sketches. In order to address this topic, this study improves a fine art drawing generation approach based on the line integral convolution techniques. To be specific, this investigation begins by segmenting the colour images through cluster analysis. Two basic colours are then assigned to each region by calculating the colour variability, and the density of each colour is calculated using a two-tone mapping technique. After that, the line integral convolution technique is applied to generate sketch textures for each of the two basic colour layers, and the two layers are fused to produce the coloured textures. At the same time, a neon transform is used to generate the sketch contour lines. Eventually, the contours are blended with the coloured textures to obtain the coloured sketch effect. The experimental results show that the art painting generation method designed in this paper is able to automatically transform from colour images to coloured pencil drawings, thus improving the efficiency of the process as well as meeting the real-time requirements.