Researchers at Oregon State University are making key advances with a new type of optical sensor that more closely mimics the human eye’s ability to perceive changes in its visual field.
The sensor described recently in Applied Physics Letters is a major breakthrough for fields such as image recognition, robotics, and artificial intelligence.
Previous attempts to build a human-eye type of device, called a retino-morphic sensor, have relied on software or complex hardware. But the new sensor’s operation is part of its fundamental design, using ultrathin layers of perovskite semiconductors which change from strong electrical insulators to strong conductors when placed in the light.
The result is that a single pixel is doing something that would currently require a microprocessor.
The new sensor will be a perfect match for the neuromorphic computers that will power the next generation of artificial intelligence in applications like self-driving cars, robots, and advanced image recognition systems. Unlike traditional computers, which process information sequentially as a series of instructions, neuromorphic computers are designed to emulate the human brain’s massively parallel networks.
People have tried to replicate this in hardware and have been reasonably successful. However, even though the algorithms and architecture designed to process information are becoming more and more like a human brain, the information these systems receive is still decidedly designed for traditional computers.
However, to reach its full potential, a computer that “thinks” more like a human brain needs an image sensor that “sees” more like a human eye.
A spectacularly complex organ, the eye contains around 100 million photoreceptors. However, the optic nerve only has 1 million connections to the brain. This means that a significant amount of preprocessing and dynamic compression must take place in the retina before the image can be transmitted.
As it turns out, our sense of vision is particularly well-adapted to detect moving objects and is comparatively “less interested” in static images. Thus, our optical circuitry gives priority to signals from photoreceptors detecting a change in light intensity - you can demonstrate this yourself by staring at a fixed point until objects in your peripheral vision start to disappear, a phenomenon known as the Troxler effect. That’s what the retino-morphic sensor does.
Applied Physics Letters, December 8, 2020, Vol. 117, Iss. 23, “A Perovskite Retinomorphic Sensor,” by Cinthya Trujillo Herrera, John G. Labram. © 2020 AIP Publishing LLC. All rights reserved.
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A perovskite retinomorphic sensor: Applied Physics Letters: Vol 117, No 23 (scitation.org)