期刊文献+

基于计算机视觉的储粮活虫检测系统硬件设计 被引量:6

Hardware Design of Detection System for Stored-grain Live Insects Based on Computer Vision
下载PDF
导出
摘要 设计了基于可见光-近红外计算机视觉的储粮活虫检测系统,该系统主要由粮虫自动分离子系统、粮虫传输子系统、光照箱、图像采集子系统4部分组成。粮虫自动分离子系统可从粮食样本中快速、有效地分离出粮虫,并进行自动除尘;粮虫传输子系统可准确接收筛下物,并输送采集盒到图像视觉采集部分的正下方以供图像采集;光照箱可为采集盒中的筛下物提供均匀的可见光-近红外波段的漫反射光;图像采集子系统可同时采集筛下物的近红外图像和可见光图像。系统对危害严重的9类储粮活虫的筛分率达到96.06%。实验验证了该系统的可行性。 The detection system for stored-grain live insects was developed based on visible-near infrared computer vision.The system included an automatic sieving subsystem of insects,an automatic transporting subsystem of insects,an illumination box and an image acquisition subsystem.The insects could be rapidly and efficiently separated from the grain sample,and removed dust automatically in the automatic sieving subsystem of insects.The automatic transporting subsystem of insects could accurately receive the sieve material,and transport the collection box to the image vision acquisition part for image acquisition.The even illumination chamber could provide even visible and near-infrared diffuse light for the sieve material in the collection box.The image acquisition subsystem could simultaneously acquire the visual image and the near infrared image of the sieve material.The sieving accuracy of the detection system was 96.06% for the nine species of the most destructive live insects.The experiment showed that the system was practical and feasible.
出处 《农业机械学报》 EI CAS CSCD 北大核心 2012年第4期193-196,167,共5页 Transactions of the Chinese Society for Agricultural Machinery
基金 国家自然科学基金资助项目(31101085 30871449) 河南省教育厅自然科学研究计划资助项目(2011B210028) 河南省高等学校青年骨干教师计划资助项目(2011GGJS-094) 华北水利水电学院高层次人才科研启动项目(201118)
关键词 储粮活虫 计算机视觉 近红外 硬件 检测 Stored-grain live insects Computer vision Near infrared Hardware Detection
  • 相关文献

参考文献9

  • 1Neethirajan S,Karunakaran C,Jayas D S,et al.Detection techniques for stored-product insects in grain[J].Food Control,2007,18(2):157-162.
  • 2张红涛.基于可见光-近红外双目计算机视觉的鞘翅目储粮害虫检测研究[D].镇江:江苏大学,2010.
  • 3Zhang H T,Mao H P.Image recognition and classification of the stored-grain pests based on support vector machine[C]∥Proceedings of Information Technology and Environmental System Sciences,2008:1 217-1 221.
  • 4耿森林,尚志远.储粮害虫声检测技术研究进展与展望[J].农业工程学报,2006,22(4):204-207. 被引量:22
  • 5Singh C B,Jayas D S,Paliwal J,et al.Detection of insect-damaged wheat kernels using near-infrared hyperspectral imaging[J].Journal of Stored Products Research,2009,45(3):151-158.
  • 6韩绿化,毛罕平,张红涛.鞘翅目储粮害虫振动筛分试验研究[J].农机化研究,2010,32(10):122-125. 被引量:1
  • 7LS/T 1211—2008粮油储藏技术规范[S].2008.
  • 8Zhang H M,Wang J.Detection of age and insect damage incurred by wheat with an electronic nose[J].Journal of Stored Products Research,2007,43(4):489-495.
  • 9毛罕平,张红涛.储粮害虫图像识别的研究进展及展望[J].农业机械学报,2008,39(4):175-179. 被引量:27

二级参考文献65

共引文献42

同被引文献72

引证文献6

二级引证文献22

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部