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Journal of Intelligent Manufacturing

, Volume 30, Issue 3, pp 1047–1055 | Cite as

Automatic inspection of salt-and-pepper defects in OLED panels using image processing and control chart techniques

  • Jueun Kwak
  • Ki Bum Lee
  • Jaeyeon Jang
  • Kyong Soo Chang
  • Chang Ouk KimEmail author
Article
First Online:
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Abstract

In the manufacture of flat display panels, salt-and-pepper defects are caused by a malfunction in the chemical process. The defects are characterized by the dispersion of many black and white pixels in the display panels; these pixels are difficult to detect with conventional automatic fault detection methods that specialize in recognizing certain shapes, such as line or mura defects (stains). This study proposes a simple but high-performance salt-and-pepper defect detection method. First, the background image of the original image is generated using the mean filter in the spatial domain to create a noise image, which is the subtraction of the two images. A binary image is then obtained from the noise image to count the defective pixels, and a statistical control chart that monitors the number of defective pixels identifies the panel defects. Two experiments were conducted with images collected from an organic light-emitting diode inspection process, and the proposed method showed excellent performance with respect to classification accuracy and processing time.

Keywords

Automated visual inspection Flat panel display Salt-and-pepper defect Image processing technique Statistical control chart 
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Notes

Acknowledgements

This work was supported in part by Samsung Display Co., Ltd., South Korea, by the Technology Innovation Program (10045913, Development of Big Data-Based Analysis and Control Platform for Semiconductor Manufacturing Plants) funded by the Ministry of Trade, Industry & Energy (MOTIE, South Korea), by the National Research Foundation (NRF) of Korea Grant funded by the Korean government (MSIP) (NRF-2016R1A2B4008337), and by the Global PhD Fellowship Program through the NRF of Korea funded by the Ministry of Education (NRF-2015H1A2A1031081).

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of Information and Industrial EngineeringYonsei UniversitySeoulKorea
  2. 2.System Engineering TeamSamsung Display Co., Ltd.AsanKorea

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