Evolved Art with Transparent, Overlapping, and Geometric Shapes
This work addresses the challenge of generating art through evolutionary algorithms for applications in digital art and creative design, but it is incremental as it builds on existing evolutionary art methods.
The paper tackled the problem of approximating images using evolved indirect encodings of transparent, overlapping geometric shapes, achieving results that aim for precision and visual appeal in artistic styles.
In this work, an evolutionary art project is presented where images are approximated by transparent, overlapping and geometric shapes of different types, e.g., polygons, circles, lines. Genotypes representing features and order of the geometric shapes are evolved with a fitness function that has the corresponding pixels of an input image as a target goal. A genotype-to-phenotype mapping is therefore applied to render images, as the chosen genetic representation is indirect, i.e., genotypes do not include pixels but a combination of shapes with their properties. Different combinations of shapes, quantity of shapes, mutation types and populations are tested. The goal of the work herein is twofold: (1) to approximate images as precisely as possible with evolved indirect encodings, (2) to produce visually appealing results and novel artistic styles.