Tech Briefs Magazine - May 2021 - PIT-5

result, SWIR cameras will work in lightstarved conditions.
For the most part, SWIR vision systems
operate in much the same way as visible
systems do. You have a target, you have a
light source, and a detector to capture the
image. The image shows up as black and
white. So, what's the difference between
imaging with monochrome cameras and
SWIR imaging? Well, SWIR light is invisible to the human eye and can detect and
highlight certain features that are difficult
or very impossible to distinguish with visible light and visible cameras. For example:
* SWIR can help differentiate between
objects that are very similar in color in
the visible spectrum;
* SWIR can help to see through certain
objects, such as silicon;
* SWIR can help see objects with very
high temperatures.

What Does SWIR Imaging
Enable?
People tend to use SWIR because they
can see different materials better. An
example that is often used is salt versus
sugar. They're both small white crystals
when viewed in the visible light, but they
have quite different reflective qualities
in the SWIR.
SWIR can also be used to look for
water content in material, which can be
beneficial for applications in agriculture, food inspection, and forestry. Any
object that contains water will absorb
SWIR wavelengths at one of two
absorption lines - one is around 1.45
microns, another one at closer to 1.8
microns. With SWIR imaging, this
enhances visibility of objects containing moisture.
With SWIR, you can generate higher
contrast images in haze, mist, rain, fog,
and other challenging atmospheric conditions due to less scattering as you move
further out into the infrared. However,
optimal effectiveness for SWIR is in a
very light fog or a very light haze; with a
heavy fog or haze, you can rely more on
heat signatures from a thermal camera.
SWIR can also detect heat, but at greater
than 300 degrees Celsius. So, this is useful for looking for defects in molten
glass and molten metal before it's
cooled.

Figure 1. The IR spectrum is divided into different regions, and each region has different applications.

camera. As a refresher, line scan cameras
scan an object line by line as it moves on
a conveyor belt or via other controlled
motion, such as taking images while flying over a stationary object. This is different from area applications, or " staring " applications where you capture an
image of the object.
It's possible to make any application
into a line scan application if you're willing to move the camera or move the
scene. A good example is apple inspection. You could take an image of the
entire apple and process that entire
image, or more effectively, you could
position the apple on a conveyor belt
going by a line scan camera and process
the data line by line which typically
results in higher resolution and processing efficiency at lower cost.

Where SWIR Shines
SWIR applications range widely from
food sorting and recycling to solar panel
inspection, agriculture, forestry, and surveillance. The benefits of SWIR imaging
are evident. We'll look at some of these
applications and discuss how SWIR
brings unique capabilities to make these
tasks easier.

Line Scan vs Area Applications
Teledyne Imaging offers both area
and line scan cameras, and in June of
2020, introduced its first SWIR line scan

Food Sorting
With SWIR imaging, we can increase
yields, reduce waste, and improve food

Photonics & Imaging Technology, May 2021

quality. SWIR imaging is best used for
high-value food sorting applications. As
an example, SWIR would typically not be
used for commodity crops like rice, but
for higher value products. SWIR is more
suitable for sorting tea leaves once
they're harvested and roasted. Because
the tea leaves are black after roasting, it
is difficult to see contaminants that may
be mixed with the tea leaves. With SWIR,
the quality inspection process can effectively identify stems, small stones, or
other debris and eliminate them from
the finished product.
Another way that we can use SWIR is
in the detection of moisture content in
food sorting, where moisture can show
spoilage or otherwise damaged produce.
For example, moisture content in fruit
indicates a bruise. The bruise would be
visible in SWIR before a human could
detect it.
SWIR can also help to differentiate
products that are similar in color
(Figure 2). In this example there are cinnamon, coffee beans, rocks, and raisins.
On the right you have a color image
where some of those items look very similar and, on the left, you can now more
clearly differentiate between these with
SWIR.
Recycling applications use similar
sorting techniques to separate different
types of materials. In plastic sorting,
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Tech Briefs Magazine - May 2021

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