Machine vision systems are playing an increasingly important role in many industrial applications, whether it is counting parts on an assembly line or examining surfaces for defects. Improvements in computing power, optics, connectivity, and software are allowing vision systems to be deployed in a wider range of applications.

Vision systems using cameras such as SICK’s IVC-3D inspect intricate surfaces such as brake pads.
Although machine vision systems have been around for several decades, their potential is not fully realized, according to Amir Novini, president and founder of Applied Vision Corp. (Akron, OH). “Machine vision remains one of the best-kept secrets - a lot of people still don’t know about them. “We’re going to see machine vision in everyday products and systems. They will become adaptable, more sophisticated. We’re working on coupling artificial intelligence to machine vision to be more forgiving and adaptive.”

Counting parts on an assembly line is a common machine vision application. But as lighting systems improve, machine vision systems are now used to search for cracks and scratches in materials in low intensity structures, according to Ben Dawson, director of strategic development at DALSA Industrial Products (Billerica, MA).

High-speed food and beverage processing operations are also increasing their use of machine vision, noted Novini. In such applications, the vision system is often required to keep up with count rates of 600 to several thousand objects per minute.

Implementing a vision system remains a somewhat daunting task, often requiring the expertise of a systems integrator. A fair amount of set-up and programming is required to train the systems to perform specific tasks. “It is hard to put together a flexible system to do more than one thing that it is assigned to, said Karl Gunnarsson, vision manager of SICK Inc. (Minneapolis, MN). “There still has to be known parts — the same parts should appear again and again. A lot of times the goal part needs certain features such as holes or other surface features.”

Nevertheless, machine vision is making impressive strides in areas such as software. “Previously, vision algorithms could only analyze two-dimensional planar surfaces. They are now looking at 3-D surfaces,” said DALSA’s Dawson.

Vision software is also becoming more flexible, with the ability to be deployed for different systems, according to John Agapakis, Machine Vision Business Manager Siemens Energy and Automation (Alpharetta, GA). “We offer the Simatic Visionscape image processing software, which allows programming for either PC-based or Smart Camera-based vision environments. You can use the same software to program different vision systems.”

Visionscape allows simultaneous viewing of several camera pictures. It can also be used for linescan applications such as checking labels on cylindrical objects like bottles.

Software advances have been accompanied by more powerful hardware. “The most noticeable difference is the speed of the computing hardware, which is several orders of magnitude faster than years ago,” said Novini.

“The progress made to provide high-performance, low-cost components has allowed broadening the scope of machine vision in more applications,” added Stephane Francois, executive vice president of Leutron Vision Inc. a Swiss-based supplier of machine vision cameras and hardware.

Some processing power now resides not on a separate vision processing board but inside the vision camera itself. No longer mere image capture devices, vision cameras are scaling up the technology curve by adding intelligence and processing capability. The enhanced cameras are sometimes referred to as “smart cameras”.

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