DocumentCode
1755789
Title
Automated Inspection of E-Shaped Magnetic Core Elements Using K-tSL-Center Clustering and Active Shape Models
Author
Huijun Gao ; Changxing Ding ; Chunwei Song ; Jiangyuan Mei
Author_Institution
Res. Inst. ofMechatronics & Autom., Bohai Univ., Jinzhou, China
Volume
9
Issue
3
fYear
2013
fDate
Aug. 2013
Firstpage
1782
Lastpage
1789
Abstract
Automated optical inspection (AOI) has been widely used in industrial Quality Assurance (QA) procedures. Multi-task inspection in high-speed AOI systems is becoming a significant problem in the design. In this paper, the design of an AOI system for E-shaped magnetic core elements is briefly described and several novel algorithms are proposed to realize defects detection by this system. First, this paper proposes a robust k-tSL-center clustering method to classify the interfaces of the element into normal and damaged areas. Second, a modified Active Shape Model (ASM) method is adopted to perform shape distortion detection in real-time. Performance evaluations are carried out on an E-shaped Magnetic Core Image Database, in which all images are captured by the designed AOI system. Experimental results show that the proposed methods are more efficient, robust and accurate than state-of-the-art methods in this application.
Keywords
automatic optical inspection; fault diagnosis; image classification; magnetic cores; pattern clustering; production engineering computing; quality control; shape recognition; AOI systems; ASM method; active shape model method; automated optical inspection; defects detection; e-shaped magnetic core elements; image capturing; industrial quality assurance procedures; k-tsl-center clustering; multitask inspection; shape distortion detection; Active shape model; Clustering methods; Inspection; Magnetic cores; Optical distortion; Robustness; Shape; Active shape models; automated optical inspection (AOI); defects detection; k-tSL-center clustering;
fLanguage
English
Journal_Title
Industrial Informatics, IEEE Transactions on
Publisher
ieee
ISSN
1551-3203
Type
jour
DOI
10.1109/TII.2013.2250294
Filename
6478808
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