Avian eye–inspired perovskite artificial vision system for foveated and multispectral imaging

Author:

Park Jinhong12ORCID,Kim Min Seok3ORCID,Kim Joonsoo12ORCID,Chang Sehui3ORCID,Lee Mincheol124ORCID,Lee Gil Ju5ORCID,Song Young Min36ORCID,Kim Dae-Hyeong127ORCID

Affiliation:

1. Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul 08826, Republic of Korea.

2. School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea.

3. School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Republic of Korea.

4. Electro-Medical Equipment Research Division, Korea Electrotechnology Research Institute (KERI), Ansan 15588, Republic of Korea.

5. Department of Electronics Engineering, Pusan National University, Busan 46241, Republic of Korea.

6. Artificial Intelligence (AI) Graduate School, GIST, Gwangju 61005, Republic of Korea.

7. Department of Materials Science and Engineering, Seoul National University, Seoul 08826, Republic of Korea.

Abstract

Avian eyes have deep central foveae as a result of extensive evolution. Deep foveae efficiently refract incident light, creating a magnified image of the target object and making it easier to track object motion. These features are essential for detecting and tracking remote objects in dynamic environments. Furthermore, avian eyes respond to a wide spectrum of light, including visible and ultraviolet light, allowing them to efficiently distinguish the target object from complex backgrounds. Despite notable advances in artificial vision systems that mimic animal vision, the exceptional object detection and targeting capabilities of avian eyes via foveated and multispectral imaging remain underexplored. Here, we present an artificial vision system that capitalizes on these aspects of avian vision. We introduce an artificial fovea and vertically stacked perovskite photodetector arrays whose designs were optimized by theoretical simulations for the demonstration of foveated and multispectral imaging. The artificial vision system successfully identifies colored and mixed-color objects and detects remote objects through foveated imaging. The potential for use in uncrewed aerial vehicles that need to detect, track, and recognize distant targets in dynamic environments is also discussed. Our avian eye–inspired perovskite artificial vision system marks a notable advance in bioinspired artificial visions.

Publisher

American Association for the Advancement of Science (AAAS)

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