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基于机器视觉的烟青虫和棉铃虫雌雄蛹的分类识别 被引量:6

Sexing of Helicoverpa assulta and Helicoverpa armigera pupae based on machine vision
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摘要 为有效分类识别烟草主要害虫烟青虫和棉铃虫的雌雄蛹,进而有效监测与防治,选取两种害虫的虫蛹作为待测样本,对害虫的图像进行分析,并结合图像处理和模式识别技术,提出一种基于机器视觉的烟草主要害虫雌雄蛹分类识别方法。利用SLR相机对两种害虫的雌雄蛹进行拍摄并提取腹部末节有效区域,获得分辨率350×350的原始图像,提取其RGB空间中R通道灰度图像作为纹理特征的输入图像,并将提取的基于灰度共生矩阵对比度、角二阶矩等纹理特征指标作为虫蛹雌雄性的判别依据,将待测试蛹特征数据输入训练好的支持向量机进行识别分类。结果表明:利用该方法实现了对烟青虫和棉铃虫雌雄蛹的较有效分类,识别率分别达到87.5%和82.5%。该方法可为害虫雌雄蛹的较准确识别提供技术支持。 In order to sex the pupae of two main tobacco pests for effective control, Helicoverpa assulta and Helicoverpa armigera, pupae images of Helicoverpa assulta and Helicoverpa armigera were analyzed based on machine vision processing with pattern recognition technology. An SLR camera was used to photograph the pupae of the two pests and the effective regions of abdominal end segments were extracted. The original images with a resolution of 350 × 350 pixel were obtained, and the gray images of the R channel in RGB space were used as the input for texture features. The extracted texture features such as contrast and angular second moment based on gray level co-occurrence matrix were taken as the basis of pupa sexing. The data of pupa features were sent to the trained support vector machine for sexing, and the results showed that this method could effectively sex the pupae of Helicoverpa assulta and Helicoverpa armigera with the recognition rates of87.5% and 82.5% respectively. This method provides a technical means for machine recognition of pest pupae.
作者 张红涛 刘迦南 谭联 朱洋 ZHANG Hongtao;LIU Jianan;TAN Lian;ZHU Yang(Institute of Electric Power,North China University of Water Resources and Electric Power,Zhengzhou 450011,China)
出处 《烟草科技》 EI CAS CSCD 北大核心 2020年第2期21-26,共6页 Tobacco Science & Technology
基金 国家自然科学基金资助项目“基于Micro-CT的单籽粒小麦内部害虫早期检测机理及方法研究”(31671580) 河南省科技攻关项目“小麦硬度的高光谱图像无损检测研究”(162102110112) 华北水利水电大学第十届研究生创新课题“基于Micro-CT的粮粒内部米象变态发育规律探究”(YK2018-11)。
关键词 烟草害虫 烟青虫 棉铃虫 雌雄性 机器视觉 支持向量机 Tobacco pest Helicoverpa assulta Helicoverpa armigera Pupa Sexing Machine vision Support vector machine
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