基于图像处理的田间杂草识别研究进展与展望
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

河北省重点研发计划项目(19227206D)、河北省引进留学人员资助项目(C201834、C201835)和河北省高等学校科学技术研究项目(QN2018081)


Review of Weeds Recognition Based on Image Processing
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    杂草是导致农作物减产的一个重要因素,准确的识别是杂草治理的前提和基础,随着计算机和信息技术的进步,机器视觉和图像处理相结合成为了当前杂草检测和识别的主流方法。本文从图像的预处理、分割、特征提取和分类4个角度,详细介绍了当前国内外田间杂草识别的研究进展以及各种分割、提取、识别方法的优缺点。另外,针对目前田间杂草检测中存在的光照环境影响、叶片的遮挡和重叠以及分类器的优化等问题进行了分析和讨论,最后根据目前杂草识别的研究趋势提出了建议与展望。

    Abstract:

    Weeds is an important factor leading to crop yield reduction, how to identify accurately is the premise and basis of weed management. With the progress of computer and information technology, the combination of machine vision and image processing has become the mainstream method of weed detection and recognition. From the point of view of image preprocessing, segmentation, feature extraction and classification, the current research progress of field weed recognition at home and abroad, as well as the advantages and disadvantages of various segmentation, extraction and recognition methods were introduced in detail. In addition, the effects of light environment, the occlusion and overlap of leaves, and the optimization of classifiers in weed detection in the field were analyzed and discussed. Finally, the suggestions and prospects for the current research trend of weed identification were put forward. 

    参考文献
    相似文献
    引证文献
引用本文

袁洪波,赵努东,程曼.基于图像处理的田间杂草识别研究进展与展望[J].农业机械学报,2020,51(s2):323-334. YUAN Hongbo, ZHAO Nudong, CHENG Man. Review of Weeds Recognition Based on Image Processing[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(s2):323-334.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2020-08-01
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2020-12-10
  • 出版日期: 2020-12-10