Robust defect detection method using reference image averaging for high-throughput SEM wafer pattern inspection system

2006 ◽  
Author(s):  
Hirohito Okuda ◽  
Takashi Hiroi
Keyword(s):  
High Throughput ◽  
Defect Detection ◽  
Detection Method ◽  
Reference Image ◽  
Inspection System ◽  
Image Averaging

scholarly journals Industrial Printing Image Defect Detection Using Multi-Edge Feature Fusion Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Bangchao Liu ◽  
Youping Chen ◽  
Jingming Xie ◽  
Bing Chen
Keyword(s):  
Defect Detection ◽  
Large Scale ◽  
Feature Fusion ◽  
Detection System ◽  
Reference Image ◽  
Inspection System ◽  
Fusion Algorithm ◽  
Illumination Variation ◽  
Image Defect ◽  
Edge Feature

Online defect detection system is a necessary technical measure and important means for large-scale industrial printing production. It is effective to reduce artificial detection fatigue and improve the accuracy and stability of industry printing line. However, the existing defect detection algorithms are mainly developed based on high-quality database and it is difficult to detect the defects on low-quality printing images. In this paper, we propose a new multi-edge feature fusion algorithm which is effective in solving this problem. Firstly, according to the characteristics of sheet-fed printing system, a new printing image database is established; compared with the existing databases, it has larger translation, deformation, and uneven illumination variation. These interferences make defect detection become more challenging. Then, SIFT feature is employed to register the database. In order to reduce the number of false detections which are caused by the position, deformation, and brightness deviation between the detected image and reference image, multi-edge feature fusion algorithm is proposed to overcome the effects of these disturbances. Lastly, the experimental results of mAP (92.65%) and recall (96.29%) verify the effectiveness of the proposed method which can effectively detect defects in low-quality printing database. The proposed research results can improve the adaptability of visual inspection system on a variety of different printing platforms. It is better to control the printing process and further reduce the number of operators.

scholarly journals PCB Electronic Component Defect Detection Method based on Improved YOLOv4 Algorithm

2021 ◽  
Vol 1827 (1) ◽  
pp. 012167
Author(s):  
Haojia Xin ◽  
Zibo Chen ◽  
Boyuan Wang
Keyword(s):  
Defect Detection ◽  
Detection Method ◽  
Electronic Component

scholarly journals A Defect Detection Method Based on Faster RCNN for Power Equipment

2021 ◽  
Vol 1754 (1) ◽  
pp. 012025
Author(s):  
Yang Cheng ◽  
Lingzhi Xia ◽  
Bo Yan ◽  
Jiang Chen ◽  
Dongsheng Hu ◽  
...  
Keyword(s):  
Defect Detection ◽  
Detection Method ◽  
Power Equipment

Defect detection method for rail surface based on line-structured light

Measurement ◽  
2020 ◽  
Vol 159 ◽  
pp. 107771 ◽  
Author(s):  
Xiaohui Cao ◽  
Wen Xie ◽  
Siddiqui Muneeb Ahmed ◽  
Cun Rong Li
Keyword(s):  
Defect Detection ◽  
Detection Method ◽  
Structured Light ◽  
On Line
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