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Proceedings Paper

Automatic organic light-emitting diode display Mura detection model based on human visual perception and multi-resolution
Author(s): Zhi-Yu Zhu; Jie-En Li; Po-Yuan Hsieh; Jian-Jia Su; Chung-Hao Tien
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Paper 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.

Paper Details

Date Published: 12 November 2019
PDF: 3 pages
Proc. SPIE 11197, SPIE Future Sensing Technologies, 111970O (12 November 2019); doi: 10.1117/12.2542638
Show Author Affiliations
Zhi-Yu Zhu, National Chiao Tung Univ. (Taiwan)
Jie-En Li, National Chiao Tung Univ. (Taiwan)
Po-Yuan Hsieh, National Chiao Tung Univ. (Taiwan)
Jian-Jia Su, National Chiao Tung Univ. (Taiwan)
Chung-Hao Tien, National Chiao Tung Univ. (Taiwan)

Published in SPIE Proceedings Vol. 11197:
SPIE Future Sensing Technologies
Masafumi Kimata; Christopher R. Valenta, Editor(s)

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