Automatic organic light-emitting diode display Mura detection model based on human visual perception and multi-resolution

Zhi-Yu Zhu; Jie-En Li; Po-Yuan Hsieh; Jian-Jia Su; Chung-Hao Tien

doi:10.1117/12.2542638

12 November 2019 Automatic organic light-emitting diode display Mura detection model based on human visual perception and multi-resolution

Zhi-Yu Zhu, Jie-En Li, Po-Yuan Hsieh, Jian-Jia Su, Chung-Hao Tien

Author Affiliations +

Proceedings Volume 11197, SPIE Future Sensing Technologies; 111970O (2019) https://doi.org/10.1117/12.2542638
Event: SPIE Future Sensing Technologies, 2019, Tokyo, Japan

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.

Citation Download Citation

Zhi-Yu Zhu, Jie-En Li, Po-Yuan Hsieh, Jian-Jia Su, and Chung-Hao Tien "Automatic organic light-emitting diode display Mura detection model based on human visual perception and multi-resolution", Proc. SPIE 11197, SPIE Future Sensing Technologies, 111970O (12 November 2019); https://doi.org/10.1117/12.2542638

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