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中国农机化学报

中国农机化学报 ›› 2023, Vol. 44 ›› Issue (12): 119-128.DOI: 10.13733/j.jcam.issn.2095-5553.2023.12.019

• 农业信息化工程 • 上一篇    下一篇

现代农业领域中计算机视觉技术的运用与发展

秦昌友1,杨艳山1,顾峰玮2,陈盼阳3,秦维彩1   

  • 出版日期:2023-12-15 发布日期:2024-01-16
  • 基金资助:
    江苏省现代农机装备与技术示范推广项目(NJ2022—17);苏州市农业自主创新项目(SNG2022061);苏州农业职业技术学院博士提升基金(BS2018);苏州市科协软科学课题立项项目

Application and development of computer vision technology in modern agriculture

Qin Changyou1, Yang Yanshan1, Gu Fengwei2, Chen Panyang3, Qin Weicai1   

  • Online:2023-12-15 Published:2024-01-16

摘要: 计算机视觉是一个涉及使机器“看到”的领域。该技术使用相机和计算机代替人眼来识别,跟踪和测量目标以进行进一步的图像处理。随着计算机视觉的发展,这种技术在现代农业领域得到广泛的应用,并在其发展中发挥关键作用。首先,详细阐述计算机视觉的概念、组成部分和工作原理。其次,介绍国内外计算机视觉技术在水产养殖、畜牧养殖、农作物生长监测、农作物病虫害监视、果蔬识别定位与采摘等领域的研究进展与应用情况。通过分析发现,现有技术可以促进现代农业自动化发展,实现低成本、高效率、高精度的优势。然而,未来技术将继续向现代农业新的应用领域拓展,需要克服的技术问题会更多。最后,系统总结和分析计算机视觉技术在现代农业的应用与挑战,探讨未来的机遇和前景,为研究者提供最新的参考。

关键词: 计算机视觉, 图像处理, 现代农业, 自动化

Abstract: Computer vision is a field that involves enabling machines to “see”. This technology uses cameras and computers instead of human eyes to identify, track, and measure targets for further image processing. With the development of computer vision, this technology has found widespread applications in modern agriculture and has played a crucial role in its advancement. Firstly, the concept, components, and working principles of computer vision are detailed. Secondly, the research progress and applications of computer vision technology in areas such as aquaculture, livestock farming, crop growth monitoring, crop pest surveillance, and fruit and vegetable recognition, positioning, and harvesting are introduced both domestically and internationally. Through analysis, it is found that existing technology can promote the development of modern agricultural automation, realizing advantages of low cost, high efficiency, and high precision. However, future technologies will continue to expand into new application areas in modern agriculture, bringing about more technical challenges that need to be overcome. Finally, the paper systematically summarizes and analyzes the applications and challenges of computer vision technology in modern agriculture, discussing future opportunities and prospects, providing the latest references for researchers.

Key words: computer vision, image processing, modern agriculture, automation

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