• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2014, Vol. 36 ›› Issue (07): 1363-1370.

• 论文 • 上一篇    下一篇

农作物病虫害图像识别技术的研究综述

汪京京1,张武1,2,刘连忠1,黄帅1   

  1. (1.安徽农业大学信息与计算机学院,安徽 合肥 230036;2.农业信息学安徽省重点实验室,安徽 合肥 230036)
  • 收稿日期:2012-12-29 修回日期:2013-05-17 出版日期:2014-07-25 发布日期:2014-07-25
  • 基金资助:

    安徽省科技攻关项目(1201a0301008);农业部948资助项目(2013Z64)

Summary of crop diseases and
pests image recognition technology               

WANG Jingjing1,ZHANG Wu1,2,LIU Lianzhong1,HUANG Shuai1   

  1. (1.College of Information and Computer Science,Anhui Agriculture University,Hefei 230036;2.Anhui Key Laboratory for Agricultural Informatics,Hefei 230036,China)
  • Received:2012-12-29 Revised:2013-05-17 Online:2014-07-25 Published:2014-07-25

摘要:

农作物病虫害的爆发往往意味着大规模的减产减质,造成不可挽回的经济损失。传统的病虫害识别方法速度慢、主观性强、误判率高,已不能满足农业生产的需要。基于图像处理技术的农作物病虫害识别具有快速、精确、实时等特点,能够协助农耕人员及时采取有效的防治措施。本文从图像分割、特征值提取和分类识别三个方面,分别阐述图像处理技术应用于农作物病虫害识别的研究现状和进展,并对今后的研究趋势和方向作了展望。

关键词: 图像处理, 病虫害, 图像分割, 特征提取, 分类识别

Abstract:

The outbreak of crop pests and diseases often means large scales of production and quality decline which can lead to irrecoverable economic losses. The traditional disease and pest identification approach is slow, subjective and not accurate, not suitable for the current agricultural production. The image processing based crop disease and pest identification is fast, accurate and realtime, and it can assist farmers to timely adopt effective preventative methods. This thesis describes the study status and progress of image processing technology’s application on crop disease and pest identification in image segmentation, feature extraction and classification, and outlooks into the future trend and direction of further studies.

Key words: image processing;diseases and pests;segmentation;feature extraction;classification and recognition