Defect Detection of Alumina Substrate with Adaptive Edge Detection Algorithm

被引:1
|
作者
Li, Chaorong [1 ,2 ]
Chen, Liangwei [3 ]
Zhu, Lihong [2 ]
Xue, Yu [4 ]
机构
[1] Minist Univ Elect Sci & Technol, Key Lab Neuroinformat, Ctr Informat BioMed, Chengdu, Sichuan, Peoples R China
[2] Yibin Univ, Dept Comp Sci & Informat Engn, Yibin 644000, Peoples R China
[3] Chengdu Aeronaut Vocat & Tech Coll, Dept Informat & Engn, Chengdu 610100, Sichuan, Peoples R China
[4] Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing, Jiangsu, Peoples R China
来源
CLOUD COMPUTING AND SECURITY, PT VI | 2018年 / 11068卷
基金
中国博士后科学基金;
关键词
Alumina ceramic; Surface defect; Defect detection; Canny algorithm; Lifting wavelet; Multilevel Otsu algorithm;
D O I
10.1007/978-3-030-00021-9_44
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Detecting surface defects of alumina substrate by using computer technique will enhance productivity in industrial manufacture. Edge detection of image is the commonly used technique for the detection of surface defects. However, it is difficult to automatically detect the surface defects of the alumina substrate since the noise and the multiple kinds of defects may exist in a substrate. In this paper, we designed an edge detection algorithm based on Canny detector aiming to automatically detect the surface defects of alumina substrate. Our algorithm can adaptively smooth image as well as adaptively determine the low threshold and high threshold. Experiments show that our algorithm can effectively and automatically detect several kinds of surface defects in the alumina substrate.
引用
收藏
页码:487 / 498
页数:12
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