7‐2: High Transmittance Under‐Display Camera Structure with COE

Xu, Cuixiang; Yao, Qi-Zhi; Li, Xiao H.; Shu, Shi; He, Wei; Xu, Zhi Q.; Dong, Li W.; Wang, Wei J.; Gao, Zhi K.; Yuan, Guang C.

doi:10.1002/sdtp.15412

Cited by 4 publications

(6 citation statements)

References 10 publications

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“…According to the sensor area, integration time, and IC-related paramete ther calculation can obtain that the optical response degree of our sensor is about fC/(lx•um 2 ). These data are higher than the previous work on using glass-based PIN under-screen scheme [4], and are also consistent with the data that we calculated on the transmittance of the stack of film layers. This proves that the in-screen sche effectively increase the semaphore and reduce power consumption compared w under-screen scheme.…”

Section: Resultssupporting

confidence: 92%

“…In addition, due to a narrower bezel, the screen-to-body ratio of OLED screens is also higher than its LCD counterpart. In order to further achieve an extremely high screen-to-body ratio for better custom experience, other mobile phone parts related with screens must also be improved in design and implementation [3,4].…”

Section: Introductionmentioning

confidence: 99%

“…Electronics 2023, 12, x FOR PEER REVIEW 2 of 14 achieve an extremely high screen-to-body ratio for better custom experience, other mobile phone parts related with screens must also be improved in design and implementation [3,4].…”

Section: Introductionmentioning

confidence: 99%

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An Image Unmixing and Stitching Deep Learning Algorithm for In-Screen Fingerprint Recognition Application

Chen,

Feng,

et al. 2023

Electronics

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The market share of organic light-emitting diode (OLED) screens in consumer electronics has grown rapidly in recent years. In order to increase the screen-to-body ratio of OLED phones, under-screen or in-screen fingerprint recognition is a must-have option. Current commercial hardware schemes include adhesive, ultrasonic, and under-screen optical ones. No mature in-screen solution has been proposed. In this work, we designed and manufactured an OLED panel with an in-screen fingerprint recognition system for the first time, by integrating an active sensor array into the OLED panel. The sensor and display module share the same set of fabrication processes when manufactured. Compared with the current widely commercially available under-screen schemes, the proposed in-screen solution can achieve a much larger functional area, better flexibility, and smaller thickness, while significantly reducing module cost. A point light source scheme, implemented by lighting up a single or several adjacent OLED pixels, instead of a conventional area source scheme as in the CMOS image sensor, or a CIS-based solution, has to be adopted since the optical distance is not long enough due to the integration. We designed a pattern for the point light sources and developed an optical unmixing network model to realize the unmixing and stitching of images obtained by each point light source at the same exposure time. After training, data verification of this network model shows that this deep learning algorithm outputs a stitched image of large area and high quality, where FRR = 0.7% given FAR = 1:50 k. In despite of a poorer quality of raw images and a much more complex algorithm compared with current commercial solutions, the proposed algorithm still obtains results comparable to peer studies, proving the effectiveness of our algorithm. Thus, the time required for fingerprint capture in our in-screen scheme is greatly reduced, by which one of the main obstacles for commercial application is overcome.

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Section: Resultssupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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An Image Unmixing and Stitching Deep Learning Algorithm for In-Screen Fingerprint Recognition Application

Chen,

Feng,

et al. 2023

Electronics

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“…One exception is that when the thickness of PI2 is 5μm, the grains in the hole are large, discontinuous and disordered. According to previous reports [11][12], FDC usually uses the method of external pixel circuit. The crystalline state of the polysilicon in the PI patterned hole is not important because there is no pixel circuit inside.…”

Section: Crystallization Test Of Polycrystalline Siliconmentioning

confidence: 99%

“…For the second challence, there have been many research papers [1][2][3][4][5][6][7][8][9], and the common solution is image restoration by deep learning. However, there are few papers focused on the first question [10][11]. In the only few papers, the emphasis is on the pixel circuit placing in external buffer area and cathode patterning, and no one mentions polyimide film (PI).…”

Section: Introductionmentioning

confidence: 99%