Open AccessDigital Image Evolution of Artwork Without Human Evaluation Using the Example of the Evolving Mona Lisa Problem
Author(s) -
Julia Garbaruk,
Doina Logofătu,
Costin Bădică,
Florin Leon
Publication year - 2021
Publication title -
vietnam journal of computer science
Language(s) - English
Resource type - Journals
eISSN - 2196-8888
pISSN - 2196-8896
DOI - 10.1142/s2196888822500075
Subject(s) - computer science , delaunay triangulation , hill climbing , evolutionary algorithm , evolutionary computation , artificial intelligence , population , context (archaeology) , algorithm , computer vision , paleontology , demography , sociology , biology
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 that 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.