Evolutionary image processing

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 EIP is a relatively computationally intensive process. Evolutionary computer vision (ECV) is an application of EIP for computer vision.^[2] It has been shown that genetic programming (GP) as a subclass of EAs is particularly useful for image processing.

^ Proceedings / 22. Workshop Computational Intelligence: Dortmund, 6 - 7. Dezember 2012. Karlsruhe: KIT Scientific Publishing. 2012. ISBN 9783866449176.
^ Ebner, Marc (2010). "Evolving Object Detectors with a GPU Accelerated Vision System". Evolvable Systems: From Biology to Hardware. Lecture Notes in Computer Science. Vol. 6274. Springer. pp. 109–120. doi:10.1007/978-3-642-15323-5_10. ISBN 978-3-642-15322-8.

[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. Lecture Notes in Computer Science. Vol. 6274. Springer. pp. 109–120. doi:10.1007/978-3-642-15323-5_10. ISBN 978-3-642-15322-8.

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