E. John McGarry
PC-based machine vision systems will give way to monolithic vision sensors with smaller, cheaper,
integrated computing devices that are simpler to implement and to network.
Most of the theoretical advances that
form the basis of modern industrial machine vision are more than 20 years old. To
confirm this assertion, one need only review the contents of Digital Picture
Processing, edited by A. Rosenfeld and A. Kak (Academic Press, Vols. 1 and 2)
and published in 1982.
A machine vision system is simply a computer capable
of image capture and processing. Therefore, it’s not surprising that the recent
history of machine vision reflects the adaptation of evolving computer technology
to commercial image processing as applied to industrial automation. This process
has passed through several stages, each heavily influenced by advances in semiconductor
and computer software technology.
During the 1970s, general-purpose mainframe
computers were coupled with image capture and display peripherals. Throughout the
1980s, mainframes gave way to dedicated computers and proprietary hardware designed
to accelerate image processing. During the 1990s, machine vision followed the prevailing
trend toward standard platform computing. High-performance microprocessors and low-cost
personal computers made most special-purpose vision hardware obsolete.
Similarly, today’s advances in
high-speed networking and mobile computing have positioned the machine vision industry
for the next step: integration of the complete machine vision system into a monolithic
network appliance. The vision system is becoming the vision sensor, a tightly integrated
system that encloses imaging, processing, memory and connectivity functions in a
single box. Such sensors have already begun to eliminate the expense and footprints
required for a computer workstation, but the next generation of sensors will deliver
performance and ease of use at a significantly lower cost.
New vision sensors
may be smaller, easier to use and less costly than computers, but another measure
by which they will succeed is connectivity. How well machine vision systems lend
themselves to networking is an important criterion.
The cost of bundling a microprocessor
into a digital camera is already small, but the increased level of circuit integration
will have, among other benefits, an inverse effect on the incremental cost of processing.
The physical size and thermal characteristics
of image processing electronics had prevented the practical realization of compact
vision sensors that could compete with PC-based machine vision systems. However,
advances in semiconductor process technology have enabled development of high-performance
digital signal processors on smaller dies that operate at lower core voltages. The
result is a new generation of processors that can deliver performance up to an order
of magnitude better, yet, amazingly, consume little if any additional power.
This is an important development because
the ability of a vision sensor to passively dissipate heat is extremely limited.
With the relaxing of package size and thermal constraints, vision sensors will vie
with PCs for the bulk of machine vision applications.
The PC/frame-grabber standard prevalent
today is burdened by both the expense and the logistics of high-speed image communication.
Integrating the processors and image capture functions into a single box reduces
the cost of hardware required to transfer images from the sensor to the processing
element. Besides being the least expensive alternative, the sensor is a simpler
solution. Its architectural simplicity translates directly into ease of use, reliability,
maintainability and reusability.
Users will begin implementing network-distributed
computing techniques to optimize the benefits of vision sensors. Distributed computing
will allow the vision sensor to become a self-sufficient network resource, supplying
platform-independent user interfaces to clients anywhere on the network, located
anywhere in the world. Point-to-point dedicated user-interface devices will gradually
In the future, users will be able to
configure and monitor their machine vision systems using everything from cell phones
to engineering workstations.
Beyond the simple client-server structure,
vision sensors will enable peer-to-peer cooperation organized to address complex
multicamera inspection and alignment tasks. Applied as elements of a larger parallel
processor, they will be scalable to match the needs of almost any application.
Expect vision sensors to become smaller,
faster and easier to integrate. Expect them to provide all of the algorithms, speed
and functionality seen in today’s PC-based machine vision systems. Finally,
expect the low cost and simplicity of vision sensors to stimulate the expansion
of the industrial machine vision market and to help create new market opportunities
for fundamental vision technology.
Meet the author
E. John McGarry is senior vice president and general
manager of Cognex’s In-Sight products group in Portland, Ore.
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