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Glass recognizes the image

13.07.2019

Automatic image recognition is one of the modern topical tasks. You have to recognize a lot: from signs and text to faces and other images. As a rule, artificial neural networks are used for this, consuming significant computing and energy resources.

The idea of researchers from the University of Wisconsin-Madison was to introduce bubbles and pieces of light-absorbing materials of various shapes into the glass plate at "strategic" places. By changing the direction of light propagation, they should eventually lead to the fact that the light from the image falling on the plate will be focused or concentrated in a certain place. Each image has its own place, which allows for recognition.

To prove the concept, the researchers developed a technology for making glass plates capable of recognizing handwritten numbers. The light emanating from the image of the number, after passing through the plate, was focused on one of nine specific spots, each of which corresponded to its own number. The resulting glass pieces successfully passed the test, even being able to distinguish between handwritten 3 and 8.

Designing glass for number recognition was similar to the process of machine learning, except in this case, real material was "trained" instead of a computer program. It was necessary to calculate the places where impurities would be introduced into the glass. In fact, such an environment produces artificial neural calculations, only not digital, but analog. Although the preliminary learning process can be laborious and computationally intensive, the glass itself is then easy and inexpensive to manufacture.

The new way of performing analog artificial neural computations by propagating light in a medium has a number of advantages. These "calculations" are inherent in the material itself, so they do not require energy and do not use any electronic devices during operation. This could open up new perspectives for low power devices. Devices "glass recognition" work in real time, literally at the speed of light. The advantage of this technology lies in its ability to instantly solve recognition problems without any power consumption. In addition, a single plate of image recognition glass can be used hundreds of thousands of times.

In the future, the researchers plan to see if their approach works for more complex tasks, such as face recognition. For example, you can use such glass as a biometric lock configured to recognize the face of only one person.

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