基于改进Canny算子的葵花籽边缘检测方法
CSTR:
作者:
作者单位:

(江南大学机械工程学院,江苏 无锡 214122)

作者简介:

徐灿(1990—),女,江南大学在读硕士研究生。E-mail:c285960150@163.com

通讯作者:

中图分类号:

基金项目:


An edge detection for sunflower seeds based on improved Canny algorithm
Author:
Affiliation:

(School of Mechanical Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China)

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:

    针对葵花籽一类不规则形体的边缘检测问题,采用传统的Canny算法有许多局限。文章对其提出三点改进:① 基于梯度统计差分的自适应阀值法,克服了传统算法在目标与背景灰度变化较大时边缘检测会丢失部分边缘的不足,有效提高信噪比;② 基于梯度方向的端点延伸法,弥补了Canny算法在连接分析后得到较多断线边缘的缺陷;③ 基于最长曲线的区域包围法,可去除背景中短小边缘,从而去除目标外围的干扰,实现葵花籽区域的精确定位。试验结果证明,在高复杂背景下改进的Canny算法在葵花籽边缘检测上取得了很好的效果。

    Abstract:

    Aiming at the edge-detection for a class of objects of irregular shape, such as sunflower seeds, but the traditional Canny algorithm has many shortcomings. This paper proposed three improvements: ① The adaptive high threshold method based on the gradient statistic difference was to overcome the problem that the traditional Canny algorithm might lose part valid edge information when the gray of goals and background in the image had a relatively wide change, which had higher signal-to-noise ratio; ② It proposed an algorithm of extending at the endpoints based on the gradient direction was made up for the defect of getting many interrupted edges after the edge link analysis of traditional Canny algorithm; ③ It proposed regional bounding algorithm based on the longest edge to remove the short edge of background for achieving the precise positioning of goals edges. The results demonstrated that improved Canny algorithm achieved good results in edge-detection of sunflower seeds in high complex background.

    参考文献
    相似文献
    引证文献
引用本文

徐灿,张秋菊.基于改进Canny算子的葵花籽边缘检测方法[J].食品与机械,2015,31(5):36-38.
XUCan, ZHANGQiuju. An edge detection for sunflower seeds based on improved Canny algorithm[J]. Food & Machinery,2015,31(5):36-38.

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:2015-03-27
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2023-03-17
  • 出版日期:
文章二维码
×
《食品与机械》
友情提示
友情提示 一、 近日有不少作者反应我刊官网无法打开,是因为我刊网站正在升级,旧网站仍在百度搜索排名前列。请认准《食品与机械》唯一官方网址:http://www.ifoodmm.com/spyjx/home 唯一官方邮箱:foodmm@ifoodmm.com; 联系电话:0731-85258200,希望广大读者和作者仔细甄别。