Role of Machine Vision in Sustainable
MAY 27, 2010
(ASIA PACIFIC) - As resource shortages continue to be the norm
in manufacturing industry, it is essential for a company to
operate in an environmentally sustainable way. One of the
Factory Automation forefront technology delivering value of
minimizing resource consumption is “Machine Vision”.
It would be difficult for a company to sustain its competitive
advantage if it solely focuses on its financial performance and
negate its social strategy from corporate strategy. Some of the
most successful global organizations are able to incorporate its
corporate strategy with its social to develop true sustainable
competitive advantages in the market, leading it to sustainable
long term financial performance and social performance.
Global warming, pollution in cities, water contamination, soil
depletion, food shortages and many other problems arise due to
our ignorance in the past to take care of the environment.
Resource shortages would continue to be the norm for several
more decades. In this situation, the manufacturing industry will
be constrained by scarcity of resources and increased costs of
raw materials such as crude oil, metals, commodities etc to
pursue their manufacturing outputs.
Only those manufacturing companies that have the capability to
operate in an environmentally sustainable way would survive. It
means embarking on systems and processes which minimize the use
of resources to produce more outputs. In layman terms, this is
principled around zero waste and zero defects management. In the
past, the Automation industry has concentrated on production
line productivity and manufacturing costs reduction as key
performance indicators. But, now it is increasingly applied to
reduce scrap, eliminate defects and to minimize resource
consumption. One forefront technologies delivering this value is
“Machine Vision”. Machine Vision is a technology that combines
human eye and judgment by camera and artificial intelligence
For example, one of the world’s top biscuit manufacturing
companies installed vision sensor in its baking line. The idea
is to detect the colour of the biscuit after baking. In the past,
the production inspector and operators were controlling line
speed and oven temperature based on colour of the biscuit coming
out of the oven. The colour of biscuit is one of the indicators
to tell if a biscuit is baked properly or not. There were
several problems arising from this arrangement as different
operators would view and interpret the colours differently and
making judgement as per their own personal experience.
company’s pursuit to maintain stringent quality, slight
deviation of biscuit colour was considered unacceptable. Since,
there was no common benchmark, the scrap rate was high. Being
one of the largest food companies in the world, the company has
an environmental policy in place that also includes efficient
use of resources. It means minimizing usage of raw material,
water and energy.
The company executives scouted for various
options and solutions and finally settled for “Vision Sensor
with Real Colour capability” technology. This is how it works,
the Real Colour Vision sensor converts colour data into numeric
digits of R, G, B. (Example, a colour is registered as R=225,
G=150, B=130) and each of it can be set to different threshold
values. With the introduction of the Vision Sensor, there were
two immediate benefits.
First, it was possible to set a clear
reference for the colour of the biscuit after baking and thus
eliminating ambiguity arising from person to person judgement.
Second, it is now possible to arrive at the required baking
condition speedily. Biscuit recipe now includes R, G and B data
from vision sensor, in addition to temperature and conveyor
speed, enabling to make close loop feedback control to achieve
required baking condition without any mistake (fig.1, fig.2).
As a result, this company has
managed to reduce its consumption of flour, sugar, dairy
products, water and energy by a significant margin. This is not
just bottom line improvement but also a contribution to the
social responsibility philosophy of the business.
Fig.1: Inspecting biscuit colour by Real Colour Vision
Fig.2: Real Colour
Sensing interactive menu
You can easily specify any colour by just clicking it on the
screen. The colour chart on the screen, that shows the colour you
have chosen, enables intuitive operation even for fine
Despite its obvious benefits, the machine vision is so far
adopted by limited industry and top players only. Some of the
identified barriers for its widespread adoption are technology
gap, cost and lack of user friendliness.
As far as the cost of machine vision is concerned, the average
price range of a complete vision system has come down
dramatically as technology advances. Similarly, user
friendliness of machine vision has improved drastically after
stand alone machine vision entered the market. Standalone vision
sensor does not require complicated integration of camera, frame
grabbers and software programming. Even though the price has
reduced and user friendliness has increased, several
applications are turned down by machine vision specialists each
year. Some of these applications if solved can realize
significant reduction in waste and contribution to environment.
This is enough motivation for machine vision producing companies
that are equally passionate about environment. While the
consumer demands for various products to be inspected by machine
vision have increased, the levels of challenges have increased
too. This is because of the gap between current technology and
the user requirements.
Machine vision has progressed from
monochrome to colour vision, camera resolution has jumped from
300K pixels to several mega pixels, and processor speeds have
increased several folds. High resolution cameras and high speed
processors cannot make any difference if the processing software
is not as powerful. For example in the case study of detecting
biscuit colour, the Real Colour Technology is the key.
Since the inception of machine vision, monochrome processing is
dominating the industry. In monochrome technology information of
colour is reduced at the time of image pick up (fig.3). Colour
information is reduced to detecting brightness only.
After several years of development, came the colour image
processing. The two most common colour technologies are colour
pick up and colour grey. In colour pick up technique, only the
selected colour is extracted from the colour image and processed,
while remaining colour from the image blackened. Colour pick
allows up to eight colours to be picked and processed
simultaneously. While in the colour grey technique, one of the
selected colour is converted to grey scale of 256 levels of
black-and-white brightness and the contrasts of specific colour
is enhanced. The problem with colour pick up technique is that
it is highly sensitive to lighting condition variation. While
the problem with colour grey is that it is limited to single
colour and processing efficiency is dependent on how colour
filter is set (fig.4). As a result, both the colour image and
colour grey are losing lots of information of the original image
after the image is picked up by a colour camera Moreover, this
technique cannot detect subtle changes in images with low
Fig.3: Differentiating Real Colour from traditional
Colour Vision converts colour image into black and white
Real Colour technology (patent pending) introduced by Omron in
2006 managed to break through the above constraints. Real Colour
technique is based on the concept of human eye where an image is
processed with lots of information. There is no information loss
either during image capturing or during processing.
Different colours are represented as different positions in the
3D RGB space (fig.5). Subtle variations in colour can be recognised by representing them as distances between different
colour pixels comprising this space.
Fig.5: Real Colour Sensing
One of the advantages of Real Colour sensing processing is stable
measurements in different inspection environments. One the other
hand the drawback is that it requires a high performance
processing chips. At the moment, Omron is using custom make Dual
Mega ARCS Engine that can do multi-processing (fig.6).
Fig.6: ARCS (Advanced Real Color Sensing)
Examples where Real Colour can make a difference
One example where Real Colour technology can make a difference is
inspecting foreign particle in connector molding (fig.7).
Real colour sensing can inspect any kinds of defects, including
oil stain. Traditional colour vision cannot detect defects that
are not defined. Another example is inspecting harness of colour
sequence (fig.8). Traditional colour vision processing using
colour pick up can only see limited colour and each colour sequence
need to be taught. Colour grey would see only one colour. But,
Real colour can see inspect any colour sequence by comparing it
with the register model.
Fig.7: Inspecting foreign particles in connector
Real Colour Sensing can inspect
foreign particles where colour of defect cannot be defined, such
as oil stain.
Traditional Vision Sensors can
detect only pre-defined colour defects. It cannot detect colour
that is not defined. Real Colour Sensing can inspect any
colour sequence by comparing it with the OK item. In case of Traditional Vision
Sensor, every kind of sequence has to be taught.
Fig.8: Inspecting Harness Colour Sequence (top), Inspecting Quality of Gold Plating
on PCB (bottom)
Real Colour technology creates wonders for colour objects but it
can do little for reflective shiny metallic objects.
Traditionally Vision specialists have been using lighting
techniques and filters to get clear images, but success is not
always guaranteed. A new technology called HDR is emerging which
utilizes software power to eliminate effects of reflection to
get clear image.
High Dynamic Range or HDR
It is said that 90% of the task in machine vision is about
capturing the clear image. One of the most difficult tasks in
machine vision is the generation of clear image for individual
inspection. Image processing becomes easy if clear images are
captured regardless of lighting variation, reflection and poor
contrast. One of the problems is also the limited dynamic range
of cameras. Luckily, one of the leading players in the market,
Omron has developed HDR technology (patent pending) to minimize
the effects of lighting condition. HDR stands for High Dynamic
HDR Image Generation Technology
Dynamic range means the imaging hardware’s ability to tell
differences in luminosity. The higher dynamic range the hardware
scores, the clearer images it can generate when imaging objects
with a strong contrast in luminosity. A machine vision processor
featuring the HDR image Generation technology takes two or more
imaging of a work piece at different levels of luminosity by
changing the shutter speed and synthesizes them into a single
image rapidly (fig.9).
Fig.9: HDR Image Generation
HDR High-Contrast Technology
An image processor loaded with HDR technology can enhance the
contrast in the area to be inspected by overlapping and
synthesizing two or more images taken at the same shutter speed.
After the synthesis, noise contents are suppressed while the
area to be inspected is amplified by integration (fig.10).
Fig.10: HDR High Contrast
HDR can make significant difference while inspecting metallic
object. One of them is punched or laser marked code on
automotive components. Fig.11 shows two individual images, left
hand side top image is facing problem of overexposure while
bottom image underexposed. As a result, both these images cannot
be utilized for processing. On the other hand, fig.11 right hand
image showing the same object captured using HDR technology. The
surface of the object as well 2D code is clearly visible with
enough contrast required for reliable processing.
Comparing conventional images against HDR images
Fig.11: Conventional image vs. HDR image
Other examples are inspecting electrical components with shiny
metallic pins and black molding body under the same lighting
condition, inspecting shiny and cylindrically curved objects
Fig.12: Conventional image vs. HDR image
Yesterday’s businesses were oblivious to their negative impact
on the environment. Today’s businesses are striving for zero
impact on the environment while ensuring profitability. After
all, sustainable manufacturing means meeting the needs of
present without compromising the ability of future generation to
meet their needs. Factory Automation industry play a critical
role by providing products, services and technologies that would
help manufacturing industries to realize sustainable
environmentally friendly operations. It is not just new business
opportunities for the industry; it is also the social
For more information about
Omron's Machine Vision, please
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