摘要
本文深入探讨了计算机视觉在农业自动化领域的应用及其影响。随着科技的不断进步，计算机视觉技术为农业领域带来了革命性的变革。本文首先概述了计算机视觉的基本原理，包括图像采集、处理、分析和识别等关键步骤，以及其在精准农业中的重要角色。随后，文章详细讨论了计算机视觉在农业自动化中的具体应用。在病虫害检测与防治方面，计算机视觉技术能够实时监测作物生长状态，及时发现病虫害，并通过精准施药降低农药使用量，提高防治效果。在作物生长监测方面，该技术能够评估作物生长状态，预测产量，为农业生产提供科学依据。在农产品品质检测方面，计算机视觉技术能够实现农产品的自动分级与分拣，提高产品质量和市场竞争力。然而，计算机视觉在农业自动化应用中也面临着一些挑战。农业环境复杂多变，图像数据量庞大且多样化，这给图像处理和识别带来了难度。此外，农民对新技术的了解和接受度低，也是推广计算机视觉技术的一大障碍。为了克服这些挑战，本文提出了一系列优化措施，包括加强图像处理和识别算法的优化、推动农业图像数据的标准化和共享、提升农民的技术接受度和使用能力等。
关键词：计算机视觉；农业自动化；病虫害检测；作物生长监测；农产品品质检测
Abstract
This paper discusses the application and influence of computer vision in the field of agricultural automation. With the continuous progress of science and technology, computer vision technology has brought revolutionary changes to the agricultural field. This paper first Outlines the basic principles of computer vision, including key steps such as image acquisition, processing, analysis and recognition, as well as its important role in precision agriculture. Then, the application of computer vision in agricultural automation is discussed in detail. In the detection and control of pests and diseases, computer vision technology can monitor the growth state of crops in real time, find diseases and pests in time, and reduce the amount of pesticides through precision application, and improve the control effect. In terms of crop growth monitoring, the technology can evaluate crop growth status, predict yield, and provide scientific basis for agricultural production. In the agricultural product quality inspection, computer vision technology can realize the automatic classification and sorting of agricultural products, improve product quality and market competitiveness. However, computer vision also faces some challenges in agricultural automation applications. The agricultural environment is complex and changeable, and the amount of image data is huge and diversified, which brings difficulty to image processing and recognition. In addition, farmers' low understanding and acceptance of new technologies is also a major obstacle to the promotion of computer vision technology. In order to overcome these challenges, this paper proposes a series of optimization measures, including strengthening the optimization of image processing and recognition algorithms, promoting the standardization and sharing of agricultural image data, and improving the technical acceptance and use ability of farmers.
Keywords： Computer vision; Agricultural automation; Pest detection; Crop growth monitoring; Agricultural product quality testing
目 录
摘要 I
Abstract II
一、绪论 1
（一）研究背景 1
（二）研究目的及意义 1
（三）国内外研究现状 1
二、计算机视觉的基本原理 3
（一）传感器与图像处理 3
（二）深度学习与模式识别 3
（三）精准农业的理论基础 3
三、计算机视觉在农业中的应用 5
（一）病虫害检测与防治 5
（二）作物生长监测 5
（三）农产品品质检测 6
四、计算机视觉在农业自动化应用中面临的挑战 8
（一）农业环境复杂多变 8
（二）图像数据量庞大且多样化 8
（三）农民对技术的了解和接受度低 8
（四）季节性和地域性限制 8
五、计算机视觉在农业自动化应用中的优化措施 10
（一）加强图像处理和识别算法的优化 10
（二）推动农业图像数据的标准化和共享 10
（三）提升农民的技术接受度和使用能力 11
（四）研发适应不同季节和地域的计算机视觉系统 11
结 论 13
参考文献 14
