基于数字图像的作物和杂草分类研究进展

Radhika Kamath, Mamatha Balachandra, Srikanth Prabhu
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摘要

农业部门的主要问题之一是杂草的控制。杂草能显著降低作物产量,造成巨大损失。有许多控制杂草的方法,如使用化学除草剂、人工除草和使用机械除草。过度使用化学除草剂除草危害环境。劳动力短缺是人工除草的主要问题。机械除草效果不佳,不适合直接播种水稻等作物。近年来,人们正在探索从数字图像中自动检测和识别杂草的技术。这有助于推荐特定的除草剂,从而减少除草剂和抗除草剂杂草的过度使用。从而有助于特定地点的杂草管理。本文综述了数字图像中作物和杂草分类的一些重要研究工作。此外,本文还对今后的研究方向进行了展望。
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Classification of Crop and Weed from Digital Images: A Review
One of the major concern in the agricultural sector is the control of weeds. Weeds are capable of reducing the crop yield significantly and thus in curhuge loss. There are many ways of controlling weeds like using chemical herbicides, manual weeding, and using mechanical weeder. Overuse of chemical herbicides for weeds harms environment. Shortage of labors is a main problem with manual weeding. Mechanical weeding is not effective and is not suitable for some of the crops like direct-seeded rice fields. In recenty ears, technology is being explored in agriculture for the automatic detection and identification weeds from the digital images. This is useful in recommending specific herbicides and thus reducing overuse of herbicides and herbicide-resistant weeds. Thus contributing to site-specific weed management. This paper reviews some of the important research works carried out for the classification of crop and weeds from the digital images. In addition, some of the important future research scopes are discussed in this paper.
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