NDLI: Robust defect detection in 2D images printed on 3D micro-textured surfaces by multiple paired pixel consistency in orientation codes

Content Provider	IET Digital Library
Author	Xiang, Sheng Liang, Dong Kaneko, Shun'ichi Asano, Hirokazu
Abstract	Defect detection is now an active research area for production quality assurance. Traditional visual inspection systems are developed by human beings, which is a time-consuming, labour-intensive, and highly error-prone process, and are therefore unreliable. To overcome these problems, the authors proposed a new method for detecting defects when printing on a 3D micro-textured surface. They utilise an orientation code as the basis to resist the fluctuations in illumination. Based on the consistency of the pixel pairs, they developed a model called multiple paired pixel consistency to represent the statistical relationship between each pixel pair in defect-free images. Finally, based on this model, they designed a defect detection method. Even with different defect sizes, illumination conditions, noise intensities, and other characteristics, the performance of the proposed algorithm is extremely stable and highly accurate, and the recall, precision, and F-measure in most of the results can reach 0.85,0.93, and 0.9, respectively. In addition, the defect detection rate can reach almost 100%. This demonstrates that the authors' approach can achieve state-of-the-art accuracy in real industrial applications.
Starting Page	3373
Ending Page	3384
Page Count	12
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 14, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/14
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0724
Journal	IET Image Processing
Publisher Date	2020-08-24
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	3D Microtextured Surface Automatic Optical Inspection Computer Vision Computer Vision And Image Processing Technique Defect Detection Rate Defect Sizes Defect-free Image Error-prone Process Feature Extraction Image Texture Industrial Application of IT Inspection And Quality Control Labour-intensive Multiple Paired Pixel Consistency Optical, Image And Video Signal Processing Orientation Code Pixel Pair Production Engineering Computing Production Quality Assurance Quality Assurance Quality Control Robust Defect Detection Statistical Analysis Statistics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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