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 and Chang Ouk Kim ()
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Jueun Kwak: Yonsei University
Ki Bum Lee: Yonsei University
Jaeyeon Jang: Yonsei University
Kyong Soo Chang: Samsung Display Co., Ltd.
Chang Ouk Kim: Yonsei University

Journal of Intelligent Manufacturing, 2019, vol. 30, issue 3, No 5, 1047-1055

Abstract: 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 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10845-017-1304-8

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