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GigE Vision Interfaces Deliver Higher Performance for Machine Vision Systems
The increasing performance and density of today’s vision systems is placing demands on
bandwidth and preprocessing. Higher speed 10 GigE Ethernet interface devices and FPGAs for
preprocessing vision data can increase the ease and reduce the cost of upgrades.
by John Phillips, Pleora Technologies
As price pressures increase due to global competitiveness and economic retraction, productivity
remains an evergreen focus for the manufacturing industry. Machine vision, with its ability to
emulate and even supersede the human eye in a manufacturing process, has long been considered
a means for achieving greater productivity.
In the early 1990s, efforts to integrate machine vision were, however, largely disappointing since
they were plagued by complex programming requirements, difficult installations, mediocre
functionality, vendor-specific interfaces and low reliability. The promise of enhanced quality and
productivity, however, kept the desire for machine vision alive, particularly in the semiconductor
and electronics manufacturing sectors. In time, products matured, functionality increased and the
cost and complexity of machine vision systems came down. Today, virtually all sectors of
manufacturing have adopted machine vision systems – from food processing and paper
inspection to metal fabrication and pharmaceuticals.
Machine vision offers important advantages over human vision in terms of cost, speed, precision
and physical demands. A machine vision system can verify if an object meets a quality standard
using a variety of activities:
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Determining location, orientation and position;
Measuring dimensions within thousandths-of-an-inch accuracy;
Counting items such as pills in a bottle; or
Inspecting and identifying flaws.
The sophistication of quality inspection systems has grown to such a degree that they can offer
manufacturers 100 percent inspection rate, reduced operating costs, shorter time from production
to market, less waste, and fewer manpower requirements. With such attractive benefits, it’s no
surprise that manufacturers are keen to further capitalize and enhance the performance of their
quality inspection systems.
External market conditions are also influencing this desire for ever-growing performance levels.
Recent and emerging regulatory requirements, particularly in the food and pharmaceutical
sectors, are resulting in a need for more elements to inspect as well as deeper levels of
inspection. To avoid escalating inspection costs, next-generation machine vision systems will
employ higher resolution cameras and will not only need to process data faster, but also process
data for a single object from multiple data sources. For example, a pill could be inspected from
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multiple camera angles using multispectral imaging as well as through the use of visible light
imaging.
High-performance, Ethernet-based video interfaces and in-line FPGA image processing are two
of the tools available to today’s vision system designer that allow him/her to enhance the
flexibility and performance of quality inspection systems. When these are used in combination,
designers can optimize the use of overall system resources by bringing basic image processing
routines closer to the point of image capture, and by efficiently distributing or consolidating the
remaining processing tasks using a high-performance video network.
High-Performance Video Networks
Real-time functionality in quality inspection systems is often achieved using a direct link. This,
however, limits the topology to point-to-point connections between a vision sensor and an image
capture board or frame grabber in a PC (Figure 1). There are often advantages to being able to
view images on more than one display or process them on more than one PC. However, this
requires the configuration of additional point-to-point connections on extra PCs, display
controllers and other pieces of specialized hardware.
Consequently, point-to-point connections – used in machine vision-centric interfaces such as
Camera Link and CoaXPress - can be costly to install, difficult to manage and expensive to scale.
Moreover, as sensors continue to evolve to higher resolutions and faster frame rates, the high
bandwidth needed for real-time image transfer becomes a limiting factor.
Ethernet, on the other hand, offers exceptional networking flexibility, supporting almost every
conceivable connectivity configuration, including point-to-point, star (point-to-multipoint), and
mesh (multipoint-to-multipoint). As the primary standard deployed in most of the world’s
networks, including those for demanding military and industrial applications, Ethernet is
supported by a well-understood infrastructure based on cost-effective and non-proprietary chip
sets, switches and cabling.
Gigabit Ethernet, the widely deployed third generation of the standard, delivers 1 Gbit per
second, while the fourth generation, 10 GigE, delivers ten times that speed. Additionally,
different traffic rates between 10 Mbit/s up to 10 Gbit/s can be handled by the same switch,
ensuring backward compatibility and permitting system upgrades without sacrificing legacy
cameras already in place.
The cost savings that come with using standard, off-the-shelf Ethernet components are an
attractive add-on benefit to Ethernet’s greater design flexibility, which allows more—and
simpler—configuration and distribution options.
The GigE Vision Standard
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Initially, interest from the machine vision sector centered on Ethernet’s ability to offer longer
cable reach than the common interfaces of the day. Ethernet allows spans of up to 100 meters
between network nodes over standard, low-cost Cat 5/6 copper cabling, and much greater
distances with switches or fiber. More recently, the ability to build high-performance video
networks has been recognized as a dominant advantage, offering the flexibility to combine
various image acquisition and processing elements, connected through a variety of network
topologies.
The potential benefits of Ethernet for industrial vision applications led to the 2006 introduction
of GigE Vision, a global open standard governing the distribution of video and control data over
Ethernet networks. It establishes a standardized environment for the delivery of networked video
applications based on switched client/server Ethernet architectures. Figure 2 shows an example
of a GigE Vision enabled quality inspection system.
The standard defines four main areas that are specific to machine vision networked systems
(Figure 3). Importantly, GigE Vision leverages about 25 existing industry standards rather than
introducing proprietary schemes. These include IEEE 802.3 (Ethernet), IEEE 1588 (time
synchronization), IETF RFC2026 (jumbo frames) and EMVA GenICam (XML device
description file).
The recent inclusion of 40 GigE and 100 GigE in the IEEE 802.3 standard is a significant
indicator of the expected long-term investment in Ethernet networks. Market studies show that
the number of 1G, 10G, 40G and 100G network ports shipped on service provider and enterprise
equipment in 2010 jumped 43 percent. Also of significance is that the Ethernet access device
market is forecast to grow at an 18 percent compound annual growth rate from 2010 to 2015 as a
direct reflection of growing Ethernet connections.
This is a strong endorsement of the future of Ethernet networked technology. While the
deployment of other non-networked technologies appears to be flat or in decline, Ethernet’s
healthy outlook bodes well for the next generation of networked vision applications.
With the release of the latest update to the standard, GigE Vision 2.0, formal support for mixed
GigE and 10 GigE networks is provided. This provides two major advantages to system
designers that leverage the GigE Vision standard: modular expansion of existing systems to
accommodate higher-resolution and/or faster frame rates, with little to no rework of existing
processing software.
Using switches from a variety of big-name manufacturers (Cisco, Juniper, D-Link and others), a
mix of GigE and 10 GigE equipment can be reliably used in the same system. Devices that
convert legacy camera interfaces—such as Camera Link—into GigE Vision are also widely
available, providing additional flexibility where needed.
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During an upgrade, an Ethernet system using GigE software and drivers can be largely, if not
entirely, migrated up to 10 GigE. The elimination of software redevelopment or purchase
dramatically brings down the cost, as well as reduces the complexity of migrating to a higher
performing system. In addition to re-using software and drivers, GigE cameras can also be easily
re-employed and 10 GigE interfaces brought on-line on an as-needed basis. Last but not least,
FPGA architectures also remain largely unaffected during an upgrade, with clear migration paths
from one FPGA family to another. With an Ethernet-based quality inspection system, one can
avoid the “forklift” upgrades common to interfaces which are backwards-compatible in name
only.
Owners of quality inspection systems who are seeking higher performance levels can use the
benefits provided by Gigabit Ethernet to increase the performance of new and existing machine
vision systems. However, it is inevitable that performance requirements will continue to grow,
rather than retract, and Ethernet-based systems (both 1 GigE and 10 GigE) are ideal for futureproofing, with simple migration possible on the hardware, software and system component level.
As they continue to evolve, video networks incorporating the GigE Vision standard will serve as
important technology platforms for machine vision applications, enabling real-time display,
processing and storage. Their broad range of attributes appeals to many manufacturers due to the
advantages of versatile system design, universal adoption, and cost-effective infrastructure.
Further, the GigE Vision interface offers excellent interoperability and international
standardization.
In-Line Image Processing and Control using FPGAs
In comparison to traditional machine vision systems, a GigE Vision-based system requires no
PC-based frame grabber. While this means that no image capture hardware is required on the
(PC) receive side, real-time system-level requirements remain. To meet these requirements,
highly-tuned software and drivers can help on the PC side, while FPGAs can help on the camera
side.
In fact, there are two often-overlooked areas in which FPGAs can play a vital role. The first is in
pre-processing at the camera level. Five years ago, the amount of bandwidth needed to stream
data in real time from a high-performance image sensor seldom exceeded 1 Gigabit per second.
Since then, improvements in semiconductor processes and circuit design have yielded steady
increases in sensor densities and frame rates. In many cases, it is not necessary - or even
desirable - to have all of this data sent across the Ethernet link to the PC. For this reason, many
camera manufacturers are choosing to add pre-processing capabilities into their cameras. These
capabilities include laser triangulation and edge detection. Due to the high throughput and
determinism requirements of most quality inspection systems, these tasks are not well-suited to a
microcontroller or a DSP. With pre-processing taking place at the camera-level, the PC is
relieved of these tasks and can then concentrate on analyzing the object’s quality.
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The second area in which FPGAs can play a critical role in optimizing a system’s performance is
the triggering aspect. Newer line scan cameras operate at 100 KHz (100,000 lines per second).
Triggering, which ensures that all cameras looking at an object capture imagery at precisely the
same time, must be done with sub-millisecond accuracy. Certainly a PC cannot achieve this, and
while this was typically done by an FPGA on the frame grabber, this aspect of control is now the
domain of the camera. IEEE 1588 and GigE Vision protocols are implemented in the FPGA to
achieve this level of precision timing and accuracy.
With pre-processing and triggering, we can see that FPGAs are increasingly doing more at the
camera level. At the same time, cameras are getting smaller and are required to use power-over
cable technologies, such as Power over Ethernet (PoE), which has a maximum of 13W.
However, this maximum might be restated to 7W or less in order to keep the camera size as
small as possible. To overcome these challenges while still optimizing performance, low power
FPGAs, such as Altera’s Cyclone family, can be integrated into the system’s cameras.
The vision system designer of today is tasked to constantly increase performance while lowering
cost. While this same designer might have a box full of tools, it can often be difficult to
determine which tool or combination of tools will prove most effective for achieving these goals
—especially over the long-term. The selection of high-performance, Ethernet-based video
interfaces and IP, as well as in-line FPGA image processing, are a practical place to start. When
used in combination with a long life cycle FPGA like Cyclone V FPGAs, designers can optimize
the use of overall system resources by bringing basic image processing routines closer to the
point of image-capture, and by efficiently distributing or consolidating the remaining processing
tasks using a high-performance video network, as illustrated by Figure 2. Furthermore, with the
use of FPGA, Ethernet-based systems can scale with increasing video bandwidth and preprocessing performance and can be seamlessly migrated from 1 GigE to 10 GigE, which
significantly extends the lifespan of a system.
Pleora Technologies, Katana, ON, Canada. (613) 270 0625. [www.pleora.com].
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