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Evoboard: Geoboard-Inspired Evolved Typefonts

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Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14633))

Abstract

Type design is a field that deals with the creation of visually appealing designs for the written language. The work of the designer is time-consuming and requires many iterations until the final solution is achieved. Although a human expert is required to validate the final results, this task can be aided by automatic design software. We propose Evoboard, an automatic algorithm that evolves a typefont using a geoboard-inspired representation where each character is a self-intersecting polygon. Evoboard uses a genetic algorithm to optimize the number of vertices of the polygon and their positions in a grid. The evolution of the population is guided by an Optical Character Recognition (OCR) model that aims to maximize the recognition of the polygon as the target character. Thanks to this simple pipeline, both the OCR model and the representation can be easily modified by the user to their needs. We evolve a set of 36 alphanumeric characters that are both highly legible and aesthetically appealing, two important aspects of type design.

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Notes

  1. 1.

    Implementation available at www.github.com/jespb/Evoboard.

  2. 2.

    In the fixed-length Evoboard variant, the length is always set to 11.

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Acknowledgments

Work funded by FCT through the LASIGE R &D Unit, UIDB/00408/2020 [11] and UIDP/00408/2020 [12] — CISUC R &D Unit, UIDB/00326/2020 [9] and UIDP/00326/2020 [10]; ValgrAI: Valencian Graduate School and Research Network for Artificial Intelligence [31]; and Generalitat Valenciana.

We would also like to thank the Society for the Promotion of Evolutionary Computation in Europe and its Surroundings (SPECIES) for the opportunity to participate in the SPECIES Summer School 2023, which took place in Moraira, Spain, between the 3rd and 9th of September, where this work originated.

Author information

Authors and Affiliations

  1. LASIGE, Faculty of Sciences, University of Lisbon, Lisbon, Portugal

    João Eduardo Batista

  2. School of Informatics, University of Edinburgh, Edinburgh, UK

    Fraser Garrow

  3. University of Alicante, Alicante, Spain

    Carlo Huesca-Spairani

  4. CISUC, DEI and LASI, University of Coimbra, Coimbra, Portugal

    Tiago Martins

Authors
  1. João Eduardo Batista
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  2. Fraser Garrow
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  3. Carlo Huesca-Spairani
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  4. Tiago Martins
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Corresponding author

Correspondence to João Eduardo Batista .

Editor information

Editors and Affiliations

  1. University of Nottingham, Nottingham, UK

    Colin Johnson

  2. University of Coimbra, Coimbra, Portugal

    Sérgio M. Rebelo

  3. University of Coruña, Coruña, Spain

    Iria Santos

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Batista, J.E., Garrow, F., Huesca-Spairani, C., Martins, T. (2024). Evoboard: Geoboard-Inspired Evolved Typefonts. In: Johnson, C., Rebelo, S.M., Santos, I. (eds) Artificial Intelligence in Music, Sound, Art and Design. EvoMUSART 2024. Lecture Notes in Computer Science, vol 14633. Springer, Cham. https://doi.org/10.1007/978-3-031-56992-0_2

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  • DOI: https://doi.org/10.1007/978-3-031-56992-0_2

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