2017/03/10 by Neumann, Aneta, Szpak, Zygmunt L., Chojnacki, Wojciech +1
#FOS: Computer and information sciences #Neural and Evolutionary Computing (cs.NE)
paper · doi:10.48550/arxiv.1703.03773
Evolutionary algorithms have recently been used to create a wide range of artistic work. In this paper, we propose a new approach for the composition of new images from existing ones, that retain some salient features of the original images. We introduce evolutionary algorithms that create new images based on a fitness function that incorporates feature covariance matrices associated with different parts of the images. This approach is very flexible in that it can work with a wide range of features and enables targeting specific regions in the images. For the creation of the new images, we propose a population-based evolutionary algorithm with mutation and crossover operators based on random walks. Our experimental results reveal a spectrum of aesthetically pleasing images that can be obtained with the aid of our evolutionary process.