Computer Engineering and Applications ›› 2015, Vol. 51 ›› Issue (20): 167-171.

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Research on recognition of tobacco leaf disease based on computer vision

YU Yong1, ZHANG Yunwei1, WANG Jing2, WANG Dalong2, WANG Yanjun2, BAO Jun1   

  1. 1.Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
    2.Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China
  • Online:2015-10-15 Published:2015-10-30


喻  勇1,张云伟1,王  静2,王大龙2,王彦钧2,包  俊1   

  1. 1.昆明理工大学 信息工程与自动化学院,昆明 650500
    2.昆明理工大学 现代农业工程学院,昆明 650500

Abstract: To overcome the shortage of inaccuracies and subjectivity in disease artificial recognition of tobacco leaf, a fast classification algorithm based on computer image processing technology is presented for tobacco brown spot and tobacco wildfire disease in this paper. The algorithm mainly includes two parts of feature parameters extraction and disease classification. Through image analysis for these two tobacco leaf diseases, six feature parameters for disease recognition are given by optimum seek, and a standard feature library is established. Fuzzy pattern recognition algorithm based on standard feature library is used in tobacco leaf disease recognition and classification. Then, the method is compared with the fuzzy C-means clustering algorithm. The experimental results of tobacco brown spot and tobacco wildfire disease classification show that the proposed classification recognition algorithm has good rate of identification.

Key words: tobacco leaf diseases, image processing, fuzzy pattern recognition, standard feature library, fuzzy C-means clustering algorithm

摘要: 针对野外非专业人员对烟叶病害识别的不准确性和受主观因素影响的不足,以烟叶病害中常见的赤星病和野火病为研究对象,运用计算机图像处理技术提出了一种快速分类识别算法,主要包括特征参数提取和病害识别分类两部分。通过赤星病和野火病烟叶病害图像分析,优选出6个病害识别特征参数,建立了两类病害标准特征库。病害识别分类采用基于标准特征库的模糊模式识别算法,并且与模糊C均值聚类识别进行了对比。病害分类识别实验结果表明该分类识别算法具有良好的识别率。

关键词: 烟叶病害, 图像处理, 模糊模式识别, 标准特征库, 模糊C均值聚类算法