From Music to Image a Computational Creativity Approach

  • Conference paper
  • First Online:
Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART 2021)

Abstract

In this paper we propose a possible approach for a cross-domain association between the musical and visual domains. We present a system that generates abstract images having as inspiration music files as the basis for the creative process. The system extracts available features from a MIDI music file given as input, associating them to visual characteristics, thus generating three different outputs. First, the Random and Associated Images - that result from the application of our approach considering different shape’s distribution - and second, the Genetic Image, that is the result of the application of one Genetic Algorithm that considers music and color theory while searching for better results. The results of our evaluation conducted through online surveys demonstrate that our system is capable of generating abstract images from music, since a majority of users consider the images to be abstract, and that they have a relation with the music that served as the basis for the association process. Moreover, the majority of the participants ranked highest the Genetic Image.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
EUR 29.95
Price includes VAT (Germany)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 74.89
Price includes VAT (Germany)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
EUR 96.29
Price includes VAT (Germany)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    Set of five horizontal lines found on music sheets where musical notes are placed.

  2. 2.

    In musical notation, a pitch-class is the set of all pitches that are a whole number of octaves apart.

  3. 3.

    https://www.python.org.

  4. 4.

    https://www.cairographics.org/pycairo/.

  5. 5.

    MIDI message that identifies the instrumental sound the device uses when it plays a Note.

  6. 6.

    https://scikit-learn.org/stable/modules/neighbors.html.

  7. 7.

    https://python-colormath.readthedocs.io/en/latest/delta_e.html.

References

  1. Bossart, W.H.: Form and meaning in the visual arts. Br. J. Aesthet. 6(3), 259–271 (1966)

    Article  Google Scholar 

  2. Colton, S.: The painting fool: stories from building an automated painter. In: McCormack, J., d’Inverno, M. (eds.) Computers and Creativity, pp. 3–38. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31727-9_1

    Chapter  Google Scholar 

  3. Cuthbert, M.S., Ariza, C.: music21: a toolkit for computer-aided musicology and symbolic music data (2010)

    Google Scholar 

  4. DiPaola, S., Gabora, L.: Incorporating characteristics of human creativity into an evolutionary art algorithm. Genet. Program. Evolvable Mach. 10(2), 97–110 (2008)

    Article  Google Scholar 

  5. Ekman, P.: Universal emotions. https://www.paulekman.com/universal-emotions/. Accessed 02 Jan 2020

  6. Esaak, S.: The 7 elements of art and why knowing them is important. https://www.thoughtco.com/what-are-the-elements-of-art-182704. Accessed 16 July 2020

  7. Horn, B., Smith, G., Masri, R., Stone, J.: Visual information vases: towards a framework for transmedia creative inspiration. In: ICCC, pp. 182–188 (2015)

    Google Scholar 

  8. Machado, P., Cardoso, A.: All the truth about NEvAR. Appl. Intell. 16(2), 101–118 (2002)

    Article  Google Scholar 

  9. McCall, J.: Genetic algorithms for modelling and optimisation. J. Comput. Appl. Math. 184(1), 205–222 (2005)

    Article  MathSciNet  Google Scholar 

  10. Morton, J.: Basic color theory. https://www.colormatters.com/color-and-design/basic-color-theory. Accessed 01 Aug 2020

  11. Moura, L.: Robot art: an interview with Leonel Moura. In: Arts, vol. 7, p. 28 (2018)

    Google Scholar 

  12. Teixeira, J., Pinto, H.S.: Cross-domain analogy: from image to music. In: Proceedings of the 5th International Workshop on Musical Metacreation (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Luís Aleixo .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Aleixo, L., Pinto, H.S., Correia, N. (2021). From Music to Image a Computational Creativity Approach. In: Romero, J., Martins, T., Rodríguez-Fernández, N. (eds) Artificial Intelligence in Music, Sound, Art and Design. EvoMUSART 2021. Lecture Notes in Computer Science(), vol 12693. Springer, Cham. https://doi.org/10.1007/978-3-030-72914-1_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-72914-1_25

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-72913-4

  • Online ISBN: 978-3-030-72914-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Navigation