基于图像自动标注与改进YOLO v5的番茄病害识别系统  

Tomato Disease Recognition System Based on Image AutomaticLabeling and Improved YOLO v5

作　　者：张领先[1] 景嘉平 李淑菲 朱昕怡 乔琛 ZHANG Lingxian;JING Jiaping;LI Shufei;ZHU Xinyi;QIAO Chen(College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China)

机构地区：[1]中国农业大学信息与电气工程学院,北京100083

出　　处：《农业机械学报》2023年第11期198-207,共10页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家自然科学基金项目(62176261)。

摘　　要：针对作物病害识别系统功能单一,缺乏系统升级机制,人工升级系统成本较大的问题,以番茄病害为例,提出了基于OpenCV的番茄叶片图像自动标注算法和改进YOLO v5的番茄病害识别模型;结合数据集自动划分、模型自动训练与评估、手机APP自动创建与更新理念,设计了一种可以自动升级的番茄病害识别系统;引入专家审查校正机制,提高了系统识别结果的可靠性。实验结果表明,该系统实现了对番茄的健康叶片与9类病害叶片进行识别,可以在实际应用中通过手机APP识别番茄病害的同时自动扩充番茄病害图像数据集,并根据数据扩充量自动启动系统的升级优化流程,由此不断提升该系统的番茄病害识别性能。该系统为番茄生产提供了一个便捷、可靠的番茄病害识别工具。Intelligent recognition of crop diseases is a hot topic in the intersection of artificial intelligence and agriculture.At present,the crop disease identification system has a single function and lacks a system upgrade mechanism,and the cost of manual upgrade system is large.To solve the above problems,tomato disease was taken as an example,automatic tomato leaf image labeling algorithm was proposed based on OpenCV and an improved YOLO v5 tomato disease recognition model was constructed.Combining the ideas of automatic data set division,automatic model training and evaluation,and automatic creation and update of mobile phone APP were combined,and a tomato disease recognition system that can be automatically upgraded was designed.The expert review and correction mechanism was introduced to improve the reliability of the system identification results.The experimental results showed that the system realized the identification of the healthy leaves of tomato and the nine kinds of disease leaves,it can automatically expand the tomato disease image data set while identifying tomato diseases through the mobile phone APP in practical application,and automatically start the upgrade and optimization process of the system according to the number of data expansion,so as to continuously improve the tomato disease recognition performance of the system.The design of the system can provide a convenient and reliable tool for tomato disease identification in tomato production.

关 键 词：番茄 神经网络 自动标注 病害识别 专家审查 自动升级 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]