Jump to content

Evolutionary image processing

From Wikipedia, the free encyclopedia
This is an old revision of this page, as edited by Geysirhead (talk | contribs) at 16:17, 2 January 2025. The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

Evolutionary image processing (EIP) is a sub-area of digital image processing.[1] Evolutionary algorithms (EA) are used to optimize and solve various image processing problems. Evolutionary image processing thus represents the combination of evolutionary optimization and digital image processing. EAs have been used for several decades in computer science to optimize various problems. The application in image processing, on the other hand, is still a relatively new field of research. This is primarily due to the technological development of computer systems, as EB is a relatively computationally intensive process. Evolutionary computer vision (ECV) is an application of EIP for computer vision.[2]

References

  1. ^ Proceedings / 22. Workshop Computational Intelligence: Dortmund, 6 - 7. Dezember 2012. Karlsruhe: KIT Scientific Publishing. 2012. ISBN 9783866449176.
  2. ^ Ebner, Marc (2010). "Evolving Object Detectors with a GPU Accelerated Vision System". Evolvable Systems: From Biology to Hardware. Springer: 109–120. doi:10.1007/978-3-642-15323-5_10.