首页    期刊浏览 2025年02月19日 星期三
登录注册

文章基本信息

  • 标题:Detection and Classification of Plant Diseases Using Image Processing and Multiclass Support Vector Machine
  • 本地全文:下载
  • 作者:Murtaza Ali Khan
  • 期刊名称:International Journal of Computer Trends and Technology
  • 电子版ISSN:2231-2803
  • 出版年度:2020
  • 卷号:68
  • 期号:4
  • 页码:5-11
  • DOI:10.14445/22312803/IJCTT-V68I4P102
  • 出版社:Seventh Sense Research Group
  • 摘要:Identification of plant disease is very important to prevent the loss and keep the harvest healthy. Determination of plant disease via visual monitoring is difficult and time consuming. In this paper, we described a method of detection and classification of plant disease using image processing and machine learning techniques. We used standard images of leaves of several types of plants to test our method. Initially, our method segments the input image to isolate disease parts of the leaf. Then we obtain various features from the diseased affected segmented image. Finally, we classify leaves into healthy and disease types based on its features using Multiclass Support Vector Machine (SVM) classifier. Experimental results indicate that our method yields very high accuracy rate for detection and classification of plant diseases.
  • 关键词:Detection; Classification; Plant Diseases; Image Processing; and Multiclass Support Vector Machine
国家哲学社会科学文献中心版权所有