棉花异性纤维图像特征提
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:


Feature Extraction of Cotton Foreign Fibre
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:

    针对棉花加工过程中存在的异性纤维,采用机器视觉技术,通过图像处理方法提取异性纤维目标,采集异性纤维特征数据,应用一种改进型粗糙集理论,进行异性纤维图像目标特征向量的提取,得到有效的特征向量。最后采用决策树理论,利用提取的特征向量进行识别,实验表明,所提取的特征向量对于识别棉花异性纤维是有效的,识别率达到

    Abstract:

    95%。 For the existence of foreign fibre during cotton processing, machine vision technology and image processing were used in order to not only extract foreign fibre goals, but also collect characteristic data of foreign fibre. Decision tree theory and feature vectors extracted were used to recognize foreign fibre after eigenvectors of aimed foreign images were effectively extracted through an improved version of rough set theory. Experimental results showed that feature vectors extracted from the image of foreign fibre for the identification of cotton foreign fibre was effective and the recognition rate reached more than 95%.

    参考文献
    相似文献
    引证文献
引用本文

刘双喜,张馨,郑文秀,王金星.棉花异性纤维图像特征提[J].农业机械学报,2010,41(3):158-162.

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: