Publication Details

Evolution of Approximate Functions for Image Thresholding

BIDLO, M. Evolution of Approximate Functions for Image Thresholding. In IEEE Symposium Series on Computational Intelligence (IEEE SSCI). Los Alamos: IEEE Computer Society, 2021. p. 1-6. ISBN: 978-1-7281-9048-8.
Czech title
Evoluce přibližných algoritmů pro prahování obrazu
Type
conference paper
Language
English
Authors
Bidlo Michal, doc. Ing., Ph.D. (DCSY)
URL
Keywords

evolution strategy, cartesian genetic programming, approximate circuit, image
thresholding

Abstract

This paper investigates the utilisation of approximate addition and
multiplication for designing image thresholding functions. Cartesian Genetic
Programming is applied for the evolutionary design of circuits using various
implementations of the approximate operations. The results are presented for
various experimental setups and compared with the case when only exact addition
and multiplication is considered. It will be shown that for some range of error
metrics of the approximate operations the evolution provides solutions that are
better than those provided by the exact operations. Moreover, the utilisation of
approximate components allows reducing the implementation area of the resulting
functions.

Published
2021
Pages
1–6
Proceedings
IEEE Symposium Series on Computational Intelligence (IEEE SSCI)
Conference
IEEE Symposium Series on Computational Intelligence 2021, Orlando, US
ISBN
978-1-7281-9048-8
Publisher
IEEE Computer Society
Place
Los Alamos
DOI
10.1109/SSCI50451.2021.9659876
UT WoS
000824464300057
EID Scopus
2-s2.0-85125795817
BibTeX 
@inproceedings{BUT182262,
  author="Michal {Bidlo}",
  title="Evolution of Approximate Functions for Image Thresholding",
  booktitle="IEEE Symposium Series on Computational Intelligence (IEEE SSCI)",
  year="2021",
  pages="1--6",
  publisher="IEEE Computer Society",
  address="Los Alamos",
  doi="10.1109/SSCI50451.2021.9659876",
  isbn="978-1-7281-9048-8",
  url="https://ieeexplore.ieee.org/document/9659876"
}
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