A Genetic Aproach for Automated Image Generation: Grayscale Image Generation | ||
| Journal of Engineering | ||
| Article 1, Volume 11, Issue 2, June 2005, Pages 393-403 | ||
| Authors | ||
| Aminna Dahim Aboud; ; a Ali Attea | ||
| Abstract | ||
| Non photorealistic rendering is a new research field in the areas of computer graphics. The goal is to give a more natural feel to computer generated images, by simulating various artistic techniques and to give the sense of an image without reproducing it. In this paper, we present a new evolutionary approach to non-photorealistic rendering of 2D black/white and grayscale images. The goal is to generate a painting that is close to a given input images. This problem can be formalized as a high-dimensional optimization problem, with local minima. We have developed a genetic algorithm that modifies the traditional uniform crossover to spread out vital genes at the expense of lethal genes rather than exchanging them between matting parents. A vital or lethal gene can be determined via a threshold field associated with each pixel gene that indicates the distance between a chromosome gene and the corresponding input image pixel. The proposed evolutionary painting framework demonstrates good results and achieves reasonable convergence. | ||
| Keywords | ||
| Genetic algorithms; Painter; SUX operator; and Gray scale images | ||
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