A Survey on Evolutionary Computation for Computer Vision and Image
Analysis: Past, Present, and Future Trends
- URL: http://arxiv.org/abs/2209.06399v1
- Date: Wed, 14 Sep 2022 03:35:25 GMT
- Title: A Survey on Evolutionary Computation for Computer Vision and Image
Analysis: Past, Present, and Future Trends
- Authors: Ying Bi, Bing Xue, Pablo Mesejo, Stefano Cagnoni, Mengjie Zhang
- Abstract summary: It aims to provide a better understanding of evolutionary computer vision (ECV) by discussing the contributions of different approaches.
The applications, challenges, issues, and trends associated to this research field are also discussed and summarised.
- Score: 6.48586558584924
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Computer vision (CV) is a big and important field in artificial intelligence
covering a wide range of applications. Image analysis is a major task in CV
aiming to extract, analyse and understand the visual content of images.
However, image-related tasks are very challenging due to many factors, e.g.,
high variations across images, high dimensionality, domain expertise
requirement, and image distortions. Evolutionary computation (EC) approaches
have been widely used for image analysis with significant achievement. However,
there is no comprehensive survey of existing EC approaches to image analysis.
To fill this gap, this paper provides a comprehensive survey covering all
essential EC approaches to important image analysis tasks including edge
detection, image segmentation, image feature analysis, image classification,
object detection, and others. This survey aims to provide a better
understanding of evolutionary computer vision (ECV) by discussing the
contributions of different approaches and exploring how and why EC is used for
CV and image analysis. The applications, challenges, issues, and trends
associated to this research field are also discussed and summarised to provide
further guidelines and opportunities for future research.
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