cameras for a sustainable future
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White paper: waste no more
Recycling with hyperspectral camera
How recycling can be more efficient
How a spectral camera can improve recycling
Examples of applications and benefits
There is more to recycle
Efficient recycling of waste into reusable raw materials
is one of the significant efforts we must take to stop global
warming and over-exploitation of natural resources. That is why
governments are setting strict requirements for recycling efficiency.
• In the EU, the target is that 65% of municipal and 75%
of packing waste is reused or recycled and a maximum of 10% is
placed to landfill by 2030 (see the graph below)
• European Commission’s Circular Plastics Alliance
contributes to achieving at least 10 million tons of recycled
plastics into new products on the EU market by 2025.
• By 1 January 2025, EU member states will set up separate
collections of textiles and hazardous waste from households.
• By 31 December 2023, EU member states will ensure that
bio-waste is either collected separately or recycled at source
• Australia recycles 11.8% while New Zealand recycles 58%
of its plastics.
According to statistics, collected waste percentages
in many European countries appear to be far above 80%. Germany,
for example, gives recycling rates of 67% for household waste, around
70% for production and commercial waste, and almost 90% for construction
and demolition waste. At the same time, there are countries where
the recovery rate is less than 40%.
However, a closer look shows that most of the collected
waste is currently used for energy production and burnt in power
plants. In other words, waste is changing the format, not reused
- we are still far away from our recycling targets. We are not exploiting
maximum recycling potential, and much of the recyclable materials
do not get recycled.
The benefits of efficient recycling are clear: recycling
conserves natural resources and reduces greenhouse gases and pollution,
as well as the use of fossil fuels in energy production: it reduces
energy consumption for about 70% for plastics, 60% for steel, 40%
for paper and 30% for glass.
What is more, it is not only about the ecological
Significant value lies in the material we waste. Efficient
sorting and recycling of different materials can turn into profit
with proper material handling methods.
Also, recycling and reusing of materials need to
be cheaper and easier than using virgin materials. This potential
is yet to be uncovered, as in many cases using natural resources
in production is less expensive than using recycled material.
With political will in place and clear benefits listed,
why are the recycling numbers still as low as they are?
Recycling can be more efficient
A typical waste management process includes the collection
of waste to a recovery facility, segregation to different waste
fractions, necessary cleaning and final classification to separate
products which are then either incinerated to produce energy, recycled
based on product type and purity, or placed to landfill.
The sorting process is a critical step in many types
of recycling, from pallets to plastics, and more. Better accuracy
means better separation of different grades of material, which results
in higher value recovery. A typical sorting process is based on
a mix of techniques and cannot rely on just one detection technology.
In many cases, the available detection technology limits the types
and the amount of the collected material that we can sort.
Today, most of the recovery or recycling plants use
different technologies from bar code readers and RGB cameras to
x-ray and eddy current systems. While they are capable technologies
to a certain extent, they are not perfect solutions as they cannot
recognise the material. For example, if a plastic bottle is missing
a label with the printed barcode, it is not possible to say if it
is PET or HDPE. Eddy current detector can sort out conductive metals
but not separate plastics or pulp. RGB camera can sort bottles to
transparent, black and coloured but is still missing the actual
material information. Consequently, we lose recyclable material
to landfill or energy production, while the recycled portion is
not pure enough for possible reuse. The poor result can also cause
a loss of profits, which makes recycling impractical or dependent
on public support.
As different waste streams require different detection
and processing methods to be recycled efficiently, current recycling
methods are not flexible, efficient, and informative enough to tackle
Currently, to make up for inadequate detection technologies,
human labor must be used to make classification on materials based
on their earlier experience and learning capability. Although this
creates jobs, they are by far not the safest and most desirable
of professions. What is more, picking waste from the stream by hand
is slow, inaccurate, and expensive and yet, separating dangerous
materials or plastic types in clear plastics bottles is still impossible.
There is also the question of ethics: waste is shipped to lower
cost countries where people - also child labor – is used to
sort materials from conveyor belts manually.
A recycling plant must have sensors capable of separating
different materials reliably and with high purity, and this is where
spectral imaging can make a difference.
How a spectral camera improves recycling?
Spectral camera technology can identify different materials accurately
and reliably based on their chemical composition. It measures
and analyzes the spectrum of light reflected from or transmitted
through the material. In the visible region, the spectrum is different
and characteristic for each colour. When measuring the spectrum
beyond the visible region called near infrared (NIR), we see that
chemically different materials have different spectrum.
So-called multispectral technology has improved the situation;
however, it has its limitations. Multispectral cameras acquire
spectral data typically with one, two or three, or in some cameras,
maximum in 8 spectral bands, meaning that in each sorting location
it identifies only a few basic materials. The purity of the result
is also often limited as there are interfering factors in the
Until now, spectral cameras that would fit the industrial environments
have not been available: industrial use of spectral imaging has
been restricted by insufficient performance of spectral cameras
in terms of speed, spatial resolution, ruggedness and connectivity,
as well as by their high cost.
The situation has now changed. The recent development has improved
both speed and resolution of spectral cameras, while their implementation
cost now meets the ROI criteria of industrial solutions. What
is more, in parallel to the spectral camera development, algorithms
and solutions for real-time processing of a large amount of data
produced by the spectral cameras are also now available.
For in-line industrial applications, a line scan type spectral
camera is the only practical and properly working solution, as
it captures the entire spectral data from each pixel in the line
precisely at the same time.
A line scan (push-broom) type spectral camera can be installed,
together with proper line illumination and the real-time data
processing solution, on existing and new sorting lines like any
line-scan camera. The material identification result, pixel by
pixel, is available through a standard interface (like Gen<I>Cam)
to commercial machine vision systems. The results can then be
used to control the air nozzles or picking robots.
A spectral camera solution provides superior performance and
several benefits in various waste treatment processes over conventional
sensor technologies, as summarised in Table 1.
When used together with other technologies, spectral cameras
make sorting more accurate by providing precise information on
material type. The latest generation of hyperspectral cameras
can increase the purity of recycled materials to close to 100%;
for example, increasing the purity of recycled plastic by even
a few percents can double its value. What is more, extracting
more recyclable material also means that we are disposing less
waste to landfill.
Unlike a multi-spectral camera with fixed spectral bands, the
spectral camera is flexible and can adapt to sorting various waste
streams. It can also adopt new sorting algorithms whenthey become
Examples of applications and benefits
Out of all the plastic manufactured, only 9% gets
recycled. 12% is incinerated for energy, and 79% goes to landfills
or nature. It is estimated that by 2050 there will be more plastic
in the oceans than fish.
Majority of non-recyclable plastic waste comes from
not being able to separate different plastic types from each other
When we sort and separate the collected plastic, we
can re-use the high-quality and valuable polymers. The main objective
in sorting is to reduce the quantity of non-targeted plastic polymers
and to reduce the number of non-plastics like paper, metal, glass,
oil, soil, or other contaminants. There may also be unwanted additives
like flame retardants within the plastic, that can be detected,
identified, and sorted with spectral cameras.
Most polymers have identifiable signatures in the
NIR spectral region and can thus be sorted. However, many of the
spectral signatures are close to each other. Here, the spectral
camera’s high spectral resolution is a key to high sorting
accuracy. With PP, PE, and PET plastics, for example, close to 99%
purity can be achieved.
Sorting of black plastics
A large fraction of recyclable plastic constitutes
of black plastics, used in particular in the automotive and electronics
industries, which have added carbon-based pigment to produce the
dark grey or black colour. Black plastic types have been notoriously
difficult to identify, and so far, there has been no reliable sensor
technique to sort these materials for reuse. Even NIR cameras struggle,
as the black carbon-based pigment absorbs practically all the NIR
Development in spectral camera technology is changing
this situation as well. In addition to NIR region, different plastics
have characteristics spectral features in the longer infrared region
(called mid-wave infrared, MWIR) where most black pigments are ‘less
black’ (less absorbing) than in the NIR region. Thus, MWIR
light can penetrate in and reflect from black materials, making
their spectral identification possible. Spectral cameras operating
in the MWIR region with required speed, resolution, and sensitivity
for industrial in-line use are now available.
With a spectral camera that operates on MWIR region,
we can sort black ABS plastics with close to 99% purity.
Below is an example of black plastics sorting measured
in a laboratory with an MWIR range hyperspectral camera Specim FX50.
Twelve pieces of ABS and PE were measured together with ten pieces
of PS (34 altogether). For each sample group, half of the samples
were shiny, and the second half with diffuse surface. The figure
below shows that samples made of ABS, PS, and PE could be accurately
Textile reuse and recycling reduces environmental
impact compared to incineration and landfilling.
Nearly 100 percent of all textiles and clothing
are somehow recyclable if they can be correctly classified and
separated based on used fiber type. One obstacle for increasing
textile recycling has been the fact that various fibers that comprise
clothing make reprocessing and recycling a challenge. Although
it is possible to use human labor for classification, this is
hardly economically feasible and pose a lot of error sources.
Spectral camera in the NIR spectral region can easily
separate the most common types of textile fractions making automatic
processing possible, for example using robotics.
The advantages of NIR spectral camera based sorting
in the textile industry are:
• Non-contact and suitable to be applied in a conveyer belt
• Gives information about both pure and mixed materials
(qualitative and quantitative sorting)
• Classification is not sensitive to used colours or dyes
• Easily configurable for different sorting lines and new
• For precise colour information, HSI can replace RGB camera
Cotton is an extremely resource-intense crop in terms of water,
pesticides, and insecticides. Using recycled cotton can lead to
significant savings of natural resources and reduce pollution
from agriculture. Some materials such as cotton and linen can
be recycled for car insulation or composted, but petroleumbased
fibers such as polyester have little chance for reuse.
Material characterization for incineration
Although material recycling percentage is increasing,
it will still be necessary to incinerate some part of non-recyclable
material. These “waste-to-energy” power plants receive
material from various sources like commerce, construction, household
and industry and use this for generating power in Refuse Derived
Fuel (RDF) power plants.
The value of RDFs is derived from the calorific content
(Image KK) – which is determined by material type. Certain
materials like glass, rock, or dirt, have zero calorific value.
Water content and ice will also affect the process.
Precise combustion process control and calorific values
can only be calculated based on proper material recognition. Hyperspectral
imaging in the NIR spectral region is capable of providing an in-line
solution for this.
We need to increase the percentage of waste that is
recycled and not just collected and burned for energy production.
To achieve this target, we need better detection systems. For instance,
robots can work 24/7 accurately and efficiently without fatigue,
handle hazardous waste, and operate flexibly for different waste
streams - yet they need a visual aid to help them reliably identify
the materials. Using hyperspectral imaging together with other technologies
and sensors is a crucial step that will help us towards our goal.
Hyperspectral camera technology as well as analysis
software are already available and in use in industrial surroundings,
and their use is expected to grow at the significant market share.
In the future, they will be extensively used and implemented due
to the growing need to solve previously unfeasible sorting tasks.
Improved sorting accuracy increases the purity of
the recycled material and as a result, the value. The percentage
of waste that can be reused will also increase as a result. All
this, with the support of political decisions, may yet bring a solution
to the overuse of our natural resources.
As the hyperspectral camera hardware has improved and will continue
to do so, it will also need algorithms, analysis software, spectral
libraries, and other machine vision sensors
to produce a complete solution that will be the future of recycling
Need a price or more information? Please
email Adept Turnkey or call our offices
Adept Turnkey Pty Ltd
are 'The Machine Vision and Imaging Specialists and distributor for Specim
products in Australia and New Zealand. To find out more about the Specim
options or any Specim product, please contact
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