CISUC - Evotype: From Shapes to Glyphs
CISUC

Evotype: From Shapes to Glyphs

Authors

Abstract

Typography plays a key communication role in the contemporary information-dense culture. Type design is a central, complex, and time consuming task. In this work we develop the generative system to type design based on an evolutionary algorithm. The key novel contributions are twofold. First, in terms of representation it relies on the use of assemblages of shapes to form glyphs. There are no limitations to the types of shapes that can be used. Second, we explore a compromise between legibility and expressiveness, testing different automatic fitness assignment schemes. The attained results show that we are able to evolve a wide variety of alternative glyphs, making the proposed system a viable alternative for real-world applications in the field of type design.

Keywords

Evolutionary Computation, Deep Neural Networks, Author Design Tools

Subject

Nature-Inspired Computation, Design

Conference

Genetic and Evolutionary Computation Conference (GECCO), July 2016


Cited by

No citations found