湖北农业科学 ›› 2018, Vol. 57 ›› Issue (11): 107-110.doi: 10.14088/j.cnki.issn0439-8114.2018.11.027

• 信息工程 • 上一篇    下一篇

基于多层卷积滤波与HSV颜色提取的茶轮斑病识别研究

陈钊, 王子辉, 赵玉清, 高彦玉, 时玲   

  1. 云南农业大学机电工程学院,昆明 650201
  • 收稿日期:2018-02-23 出版日期:2018-06-10 发布日期:2019-12-19
  • 通讯作者: 时 玲(1964-),教授,主要从事温室设备控制研究,(电子信箱)shiling64@qq.com。
  • 作者简介:陈 钊(1991-),男,河北新乐人,在读硕士研究生,研究方向为图像识别与智能控制,(电话)15687875317(电子信箱)1174014946@qq.com
  • 基金资助:
    云南省教育厅一般项目(2014c065y); 云南农业大学第五批“百名”青年学术和技术带头人培养计划

Study on the Identification of Tea Wheel Spot Disease Based on Multi-layer Convolution Filter and HSV Color Extraction

CHEN Zhao, WANG Zi-hui, ZHAO Yu-qing, GAO Yan-yu, SHI Ling   

  1. College of Mechanical and Electrical Engineering,Yunnan Agricultural University,Kunming 650201,China
  • Received:2018-02-23 Online:2018-06-10 Published:2019-12-19

摘要: 利用卷积滤波对原始图像进行显示轮廓以及锐化处理,引入了HSV模型进行颜色提取,通过二值化再次滤波完成了茶轮斑病斑区的提取,实现茶叶的茶轮斑病的快速诊断。结果表明,采用卷积滤波与HSV模型等图像处理技术能够较好地识别茶轮斑病的病斑区,对于图像清晰、面积大的病斑区识别比较精确。利用Python语言的嵌入性,为进一步实现茶叶茶轮斑病的精准喷雾系统打下了基础。

关键词: 卷积滤波, 图像处理技术, 图像滤波, 茶叶病检测, 识别

Abstract: The original image is depicted and sharpen by convolution filtering, and then put it in HSV model to obtain the image color extraction. In order to get the target area of the tea wheel spot,it is also used the image binaryzation to complete the refiltering.Finally,that is a picture rapid diagnosis of tea leaf spot disease. The results showed that the image recognition of tea leaf spot in leaves of tea leaves was finished. By using convolution filtering and HSV model image processing technology can be better identified the round spot of tea lesion area, especially the clear image,size of lesion area. Taking advantage of the embeddedness of Python language,it lays the foundation for the accurate spray system of tea tea wheel spot disease.

Key words: convolution filter, image processing technology, image filtering, tea disease detection, identification

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