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September 8, 2022

Computing Image Sensor

Vehicle accidents can happen in the blink of an eye. The time it takes camera systems in autonomous vehicles to process images is critical. Researchers are developing a first-of-its-kind technology that can make split-second assessments. Learn more on NSF's "The Discovery Files."

Credit: National Science Foundation


Computing Image Sensor

This is The Discovery Files, from the U.S. National Science Foundation.

Autonomous vehicles, designed to operate without a driver in control, must be able to quickly assess their environment to see and navigate around obstacles in the roadway to avoid accidents.

The challenge with this emerging technology is can it process the data fast enough to handle those split-second situations?

New NSF-supported advances suggest the next evolution in sensor imaging is here. Harvard researchers have developed an in-sensor image processor that can extract important features from the raw visual data gathered, without having to send it to a separate microprocessor.

The in-sensor processor is the first-of-its-kind. The research team designed it to be integrated into commercial silicon imaging sensor chips, the type used in most commercial devices where visual information must be captured, including smartphones.

The silicon-based, in-sensor processor technology could have a wide variety of real-world applications, not only in machines that collect visual data like autonomous vehicles, but also in bio-inspired applications.

Our brain's capacity to combine its sensory systems with early information processing, and the very function of its memory and computing, inspired the team to undertake this unique approach.

Discover how the U.S. National Science Foundation is advancing research at nsf.gov. And check out NSF's Discovery Files podcast, available wherever you get podcasts.

"The discovery files" covers projects funded by the government's National Science Foundation. Federally sponsored research -- brought to you, by you! Learn more at nsf.gov or on our podcast.


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