A Stanford University team (United States) has developed an extremely sensitive laser system for producing hidden object images. It reveals a study published in the journal Nature.
Experts focus on developing applications for self-employed vehicles – which do not require a driver – some of which already have similar systems based on laser technology capable of detecting objects around the car. Other possible utilities include the ability to see through the foliage or to provide rescue units with the ability to find people whose position is inhibited by sight.
The Associate Professor Gordon Wetzstein, from the same American university, and one of the research authors, stated that, even if that kind of technology “sounds like Magic”, it’s “really doable.”
Apparently, the Stanford research group is not the only one in developing laser technology methods to capture images of objects. However, where it achieves considerable progress in this field is the creation of an extremely efficient and effective algorithm for processing the final image of that object.
“A substantial challenge”
David Lindell, co-author of the study, noted that “a substantial challenge” in these techniques is to “find an efficient way to recover the three-dimensional structure of the hidden object.”
During their experiments, scientists installed a laser near a highly sensitive proton detector, which could also record a single particle of light. They aimed at a wall with laser light impulses – invisible to the human eye – bouncing on objects that were hidden behind a corner to bounce in the wall and in the detector.
According to Nature, this process currently lasts from two minutes to an hour, depending on the conditions such as illumination and reflectivity of the hidden object. Based on how well the algorithm works, it is believed that it could be accelerated to make the process almost instantaneous.
But before the system is completely ready, scientists must make it work better with daylight and moving objects, like a bouncing ball or a child running, since until now it works particularly well when they detect Reflective objects, such as road signs.
If this technology was now used in a vehicle, it could easily capture images of objects such as road signs or road signs, but could encounter difficulties in detecting people wearing non-reflective clothing. Wetzstein considered that the study represents “a big step forward” in this field which, he ventured, “I hope that benefit all.”