Title: Automatic Organic Light-emitting Diode Display Mura Detection Model based on Human Visual Perception and Multi-resolution
Authors: Zhu, Zhi-Yu
Li, Jie-En
Hsieh, Po-Yuan
Su, Jian-Jia
Tien, Chung-Hao
光電工程學系
Department of Photonics
Keywords: Mura;oraganic light emitting diode;machine vision;digital image processing;contrast sensitivity function
Issue Date: 1-Jan-2019
Abstract: Organic light emitting diode generally has serious non-uniformity phenomena due to the instability of organic processing, called Mura. In this paper, we propose an automatic Mura detection model to mimic the human perception and detect Mura pixel-wisely. First, we extract regions of interest from the original image with different sizes of windows, and then we verify these regions by SEMU criterion. Consequently, we implement human visual properties based on the contrast sensitivity function filtering and ModelFest matching to segment Mura regions. As the result, our approach can successfully detect Mura with various sizes and shapes, which could have a great impact on the display industry.
URI: http://dx.doi.org/10.1117/12.2542638
http://hdl.handle.net/11536/154069
ISBN: 978-1-5106-3112-0
ISSN: 0277-786X
DOI: 10.1117/12.2542638
Journal: SPIE FUTURE SENSING TECHNOLOGIES
Volume: 11197
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End Page: 0
Appears in Collections:Conferences Paper