Anti-distortion bioinspired camera with an inhomogeneous photo-pixel array

Changsoon Choi, Henry Hinton, Hyojin Seung, Sehui Chang, Ji Su Kim, Woosang You, Min Sung Kim, Jung Pyo Hong, Jung Ah Lim, Do Kyung Hwang, Gil Ju Lee, Houk Jang, Young Min Song (), Dae-Hyeong Kim () and Donhee Ham ()
Additional contact information
Changsoon Choi: Harvard University
Henry Hinton: Harvard University
Hyojin Seung: Institute for Basic Science (IBS)
Sehui Chang: Gwangju Institute of Science and Technology
Ji Su Kim: Institute for Basic Science (IBS)
Woosang You: Institute for Basic Science (IBS)
Min Sung Kim: Institute for Basic Science (IBS)
Jung Pyo Hong: Korea Institute of Science and Technology (KIST)
Jung Ah Lim: Korea Institute of Science and Technology (KIST)
Do Kyung Hwang: Korea Institute of Science and Technology (KIST)
Gil Ju Lee: Gwangju Institute of Science and Technology
Houk Jang: Harvard University
Young Min Song: Gwangju Institute of Science and Technology
Dae-Hyeong Kim: Institute for Basic Science (IBS)
Donhee Ham: Harvard University

Nature Communications, 2024, vol. 15, issue 1, 1-9

Abstract: Abstract The bioinspired camera, comprising a single lens and a curved image sensor—a photodiode array on a curved surface—, was born of flexible electronics. Its economical build lends itself well to space-constrained machine vision applications. The curved sensor, much akin to the retina, helps image focusing, but the curvature also creates a problem of image distortion, which can undermine machine vision tasks such as object recognition. Here we report an anti-distortion single-lens camera, where 4096 silicon photodiodes arrayed on a curved surface in a nonuniform pattern assimilated to the distorting optics are the key to anti-distortion engineering. That is, the photo-pixel distribution pattern itself is warped in the same manner as images are warped, which correctively reverses distortion. Acquired images feature no appreciable distortion across a 120° horizontal view, as confirmed by their neural-network recognition accuracies. This distortion correction via photo-pixel array reconfiguration is a form of in-sensor computing.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-50271-7 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-50271-7

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-50271-7

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().