Abstract
Non-photorealistic rendering (NPR), a research about non-photorealistic images is a major field of research in image processing. Painterly rendering is a method that creates artistic images based on photo images and important in NPR. Recently, painterly rendering methods using evolutionary algorithm are studied. Those studies have intended to optimize the process of creating artistic images by using evolutionary algorithm. Most of those studies have focused on generating and placing strokes as a painting operation. On the other hand, some researchers proposed painterly rendering methods using existing art images. They have created painting images which have unique colors and textures of existing art images, called “painting style”. We propose a new method to create artistic images based on photo images and existing art images by using Genetic Algorithm (GA). Our method operates putting the “patches” on a canvas image repeatedly as a painting operation. We generate the “patches” by copying a part of the existing art images and put them on the canvas image in mutation of GA. We exchange pixels in the same region of two canvas images in crossover of GA. In the process of optimization, our method brings the canvas image close to the photo images. Our method evolutionarily creates the painting images which have the painting styles of existing art images.
