A Survey on Evolutionary Computation for Computer Vision and Image Analysis: Past, Present, and Future Trends
这篇综述全面梳理了进化计算在图像分析任务（如边缘检测、图像分割、分类等）中的应用，讨论了其贡献、挑战和未来趋势，适合想了解该交叉领域的研究者快速把握现状。
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, analyze 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 article 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 CV (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 summarized to provide further guidelines and opportunities for future research.