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Study on Digital Image Evolution of Artwork by Using Bio-Inspired Approaches

  • Julia Garbaruk
  • Doina LogofătuEmail author
  • Costin Bădică
  • Florin Leon
Conference paper
  • 287 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12033)

Abstract

Whether for optimizing the speed of microprocessors or for sequence analysis in molecular biology—evolutionary algorithms are used in astoundingly many fields. Also the art was influenced by evolutionary algorithms—with principles of natural evolution works of art can be created or imitated, whereby initially generated art is put through an iterated process of selection and modification. This paper covers an application in which given images are emulated evolutionary using a finite number of semi-transparent overlapping polygons, which also became known under the name “Evolution of Mona Lisa”. In this context, different approaches to solve the problem are tested and presented here. In particular, we want to investigate whether Hill Climbing Algorithm in combination with Delaunay Triangulation and Canny Edge Detector that extracts the initial population directly from the original image performs better than the conventional Hill Climbing and Genetic Algorithm, where the initial population is generated randomly.

Keywords

Evolution of Mona Lisa Evolving images Evolutionary algorithms 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer Science and Engineering, Frankfurt University of Applied SciencesFrankfurt amGermany
  2. 2.Department of Computer Sciences and Information Technology, University of CraiovaCraiovaRomania
  3. 3.Faculty of Automatic Control and Computer Engineering, Gheorghe Asachi Technical University of IaşiIaşiRomania

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