An improved industrial sub-pixel edge detection algorithm based on coarse and precise location

被引：43
|
作者：
Xie, Xin [1 ]
Ge, Songlin [1 ]
Xie, Mingye [2 ]
Hu, Fengping [3 ]
Jiang, Nan [1 ]
机构：
[1] East China Jiaotong Univ, Sch Informat Engn, Nanchang, Jiangxi, Peoples R China
[2] East China Normal Univ, Sch Informat Sci Technol, Shanghai, Peoples R China
[3] East China Jiaotong Univ, Sch Civil Engn, Nanchang, Jiangxi, Peoples R China
来源：
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING | 2020年 / 11卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Edge detection; Sub-pixel; Roberts operator; Zernike moment; Otsu's method;
D O I：
10.1007/s12652-019-01232-2
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, an improved sub-pixel edge detection algorithm combining coarse and precise location is proposed. The algorithm fully considers the 8-neighborhood pixel information and keeps the Roberts operator's advantages of high location accuracy and fast speed. Meanwhile, it can effectively suppress noise and obtain better detection results. In order to solve the problem of low efficiency of the Zernike moment method in threshold selection, the Otsu's method is introduced to achieve accurate sub-pixel edge location. The experimental results show that the proposed algorithm effectively improves the detection efficiency and the detection accuracy.
引用
收藏
页码：2061 / 2070
页数：10
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