Evolutionary Image Transition and Painting Using Random Walks
Abstract
We present a study demonstrating how random walk algorithms can be used for evolutionary image transition. We design different mutation operators based on uniform and biased random walks and study how their combination with a baseline mutation operator can lead to interesting image transition processes in terms of visual effects and artistic features. Using feature-based analysis we investigate the evolutionary image transition behaviour with respect to different features and evaluate the images constructed during the image transition process. Afterwards, we investigate how modifications of our biased random walk approaches can be used for evolutionary image painting. We introduce an evolutionary image painting approach whose underlying biased random walk can be controlled by a parameter influencing the bias of the random walk and thereby creating different artistic painting effects.
Cite
@article{arxiv.2003.01517,
title = {Evolutionary Image Transition and Painting Using Random Walks},
author = {Aneta Neumann and Bradley Alexander and Frank Neumann},
journal= {arXiv preprint arXiv:2003.01517},
year = {2020}
}
Comments
Accepted for the Evolutionary Computation Journal (MIT Press). arXiv admin note: text overlap with arXiv:1604.06187