基于计算机视觉的马铃薯自动检测分
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:


Detecting and Grading Method of Potatoes with Computer Vision
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    根据大小特性,采用改进的果径法进行马铃薯的大小分级;根据外形特性,采用离心率法进行马铃薯的形状分级;根据颜色特性,采用灰度值差值法检测发芽马铃薯;根据边界特性,采用相邻采样边界点归一化半径差的方法检测畸形马铃薯,并实现了马铃薯在线综合检测分级。检测试验结果表明:系统分级结果比较稳定,分级精度达到

    Abstract:

    88.0%。An automatic detecting and grading method of potatoes with computer vision was studied. Potatoes were graded according to their size by computing the potatoes’ longest axis and potatoes were grading according to the shape by computing the eccentricities. Sprouting potatoes were detected by computing the difference values of green channel gray value and misshapen potatoes were detected by computing sampling normalized radius differences’ absolute values. A potato grading software was designed to grade potatoes by size, shape and detect at the same time. The experiments show that the result with grading method described above is steady, and its precision was up to 88.0%.

    参考文献
    相似文献
    引证文献
引用本文

郑冠楠,谭豫之,张俊雄,李伟.基于计算机视觉的马铃薯自动检测分[J].农业机械学报,2009,40(4):166-168. Detecting and Grading Method of Potatoes with Computer Vision[J]. Transactions of the Chinese Society for Agricultural Machinery,2009,40(4):166-168.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期:
  • 出版日期: