High-performance image sensors in cameras, suitable illumination wavelengths, high processing power and efficient processing software are going to be crucial if machine vision systems are to keep up with the rising automation standards.
"Commensurate advancements in lighting and illumination, lasers, lighting, processors, sensors and optics have to complement machine vision systems," reiterates Frost & Sullivan Research Analyst Vishnu Sivadevan. "Developers face the challenge of reducing set-up time and also incorporating greater enhanced functionality, scalability and upgradeability."
It is important to pay special attention to issues surrounding the expenditure and time on set-up time and installation. User-friendly features, robust integration capabilities and reduction of operator training time can drive investments in machine vision systems.
"End-users are demanding quick return on investment and are attempting to make a futuristic investment in machine vision systems, choosing judiciously from a range of products, which differ in cost and functionality," explains Sivadevan.
Advanced automation standards also require machine vision systems that are flexible and scalable across multiple products and production lines. This has given rise to compact vision systems and smart cameras that have built in image sensors and processors and are also more user friendly.
While smart cameras are replacing PC-based vision systems, the choice of architecture would depend upon the application the vision system is catering to.
"In many cases a healthy marketing system becomes necessary, by which the end-user is made aware of the future prospects for expansion or upgrades of the machine vision system," says Sivadevan.
Once vision systems are projected as being versatile and easily upgradeable, the range of applications is likely to expand beyond industries and production processes.
High-end machine vision applications are progressing from two-dimensional to three-dimensional imaging with techniques such as laser triangulation and stereovision.
For instance, Canesta Inc., manufacturers of 3D chip-based vision systems, claims that their machine vision systems have cost-effective alternatives to weight sensors and stereovision techniques in automotive applications.
Currently, researchers are also working toward the development of real- time autonomous robotic guidance using machine vision systems. Artificial intelligence technique is another emerging area for enhancing the performance of these systems.
Advances in Machine Vision Systems is part of the D944 subscription and analyzes the latest trends and advances in next-generation machine vision systems. The study focuses on the latest technologies and the trends driving the development of vision systems across a range of applications. Executive summaries and analyst interviews are available to the press.
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Keywords in this release: machine vision systems, semiconductor industry, lighting and illumination, lasers, lighting, processors, sensors, optics, automation standards, smart cameras, PC-based vision systems, three- dimensional imaging, laser triangulation, stereovision, Artificial intelligence, autonomous robotic guidance, Canesta Inc.
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