Utilizing Genetic Evolution to Enhance Cellular Automata for Accurate Image Edge Detection

EasyChair Preprint 10279

Abstract

Cellular Automata (CA) is a dynamic system with discrete time and spatial neighborhood structure which, if tuned properly, can automate image processing to a great extent and tune the CA ruleset, a Genetic Algorithm (GA) has been used. In this paper, we have worked on a GA model, trying different types of setups to come up with a better GA that should have the capability to handle any kind of 2D image. Our proposed GA shows an improvement of 21.53% and 13.7% on two different images.

Keyphrases: Cellular arrays and automata, Computer Vision., Edge and feature detection, Evolutionary computing and genetic algorithms, image processing

@booklet{EasyChair:10279,
  author    = {Farhana Akter Tumpa and Md Saydur Rahman and Md Shazid Islam},
  title     = {Utilizing Genetic Evolution to Enhance Cellular Automata for Accurate Image Edge Detection},
  howpublished = {EasyChair Preprint 10279},
  year      = {EasyChair, 2023}}