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January 23, 2025
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Detecting edges of images at the speed of light
by University of Amsterdam
Detecting edges of images at the speed of light 2D edge detection
with TPPs in a simple layer stack. Credit: ACS Photonics (2024). DOI:
10.1021/acsphotonics.4c01667
Physicists from the group of Jorik van de Groep at the UvA-Institute
of Physics have devised a new method that can be used to detect edges
of images in an extremely energy efficient and ultrafast way. The
results were recently published in the journal ACS Photonics.
The energy cost of computation and data processing has become one of
the most significant energy problems for our society. It is set to
keep increasing its footprint in the future, as software demands keep
increasing and current hardware is unable to provide a reliable
answer. As such, over the past years, research into alternative
methods of computation which are ultrafast and require minimal energy
consumption has drawn significant attention.
One method of alternative computation is known as optical analog
computing. In this method, mathematical operations are performed
using light, even before it is captured by a camera. Since optical
analog computing devices are passive--that is, they do not need
electrical power--almost no energy is consumed, and moreover, the
operation is literally done at the speed of light.
Detecting edges
In their research, together with industrial partners WITec and SCIL
Imprint Solutions, the physicists have focused on edge detection
techniques, aimed at identifying edges in images--locations where a
sudden change in brightness occurs, indicating the border of an
object that is observed. Edge detection is one of the most crucial
tasks in image processing with applications in, e.g., autonomous
vehicles.
To perform the optical analog computing, the physicists used a simple
and easy-to-fabricate stack of thin films. The method turned out to
work very well, being able to detect the edges of even very small
objects, about 1 micrometer in size.
[INS::INS]
Bernardo Dias, first author of the publication, says, "The design of
the layer stack is extremely simple compared to the complex optical
coatings that pose as the state-of-the-art. Despite this, our device
shows one of the largest numerical apertures to date, allowing us to
perform edge detection on the smallest possible targets."
An additional benefit of the method is that it can work with a large
number of light sources like lamps, LEDs or lasers, facilitating its
potential use in existing technology. The results demonstrate that
these techniques can in particular be used for high resolution
microscopy.
Since the device also highlights the edges of transparent objects
which would be invisible to a conventional bright field
microscope--think of cells--application in biological samples is also
possible.
As a next step, the researchers aim to develop switchable devices for
optical analog computing, where one can switch the mathematical
operation on and off, or where the device can switch between
different functions.
More information: Bernardo S. Dias et al, High-NA 2D Image Edge
Detection Using Tamm Plasmon Polaritons in Few-Layer Stratified
Media, ACS Photonics (2024). DOI: 10.1021/acsphotonics.4c01667
Journal information: ACS Photonics
Provided by University of Amsterdam
Citation: Detecting edges of images at the speed of light (2025,
January 23) retrieved 30 January 2025 from https://phys.org/news/
2025-01-edges-images.html
This document is subject to copyright. Apart from any fair dealing
for the purpose of private study or research, no part may be
reproduced without the written permission. The content is provided
for information purposes only.
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Get Instant Summarized Text (Gist)
A new method for edge detection in images has been developed using
optical analog computing, which operates at the speed of light and
consumes minimal energy. This technique employs a simple stack of
thin films to detect edges as small as 1 micrometer, offering a large
numerical aperture. It is compatible with various light sources and
can enhance high-resolution microscopy, including applications in
biological samples by highlighting transparent objects.
This summary was automatically generated using LLM. Full disclaimer
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