The field of machine vision continues to expand dramatically, propelled by astonishing advances in related fields like artificial intelligence. Machine vision systems essentially allow computers to “see” and process images; when combined with AI, industrial image processing can revolutionize capabilities in fields like healthcare, manufacturing, and agriculture. This accounts for the sector’s growth, which is expected to reach $12.29 billion globally by the year 2023.

Rising demand meets decreasing cost

The global economy relies increasingly on automation and on integration. Smart factories and warehouses are becoming the norm; the Internet of Things and the rapid growth of AI have created dense connections between different fields. All of this makes for a significant boost in the demand for machine vision tools, which can provide and share image analysis at a speed that was previously unheard of.

At the same time, as the industry comes into its own, costs are already being driven down. A rise in competition has led to less-expensive production for component parts, which in turn puts the system within the reach of more businesses. This trend is expected to continue, or even to snowball, especially as industrial image processing becomes standard practice in more sectors.

Cameras and software

A series of recent mergers and acquisitions has meant drastically lower costs for cameras and their component parts. Consolidations between companies that produce machine vision cameras and firms which specialize in advanced visible imaging have made equipment far more affordable.

A few such mergers stand out. Omron Corporation, a leader in the field of automation, acquired Sentech in 2017. The merger is notable in part because it gave Omron access to Sentech’s expertise in ultra-compact, high speed camera technology, which married naturally with Omron’s high-speed image processing technology. Omron was able to begin work on a revolutionary new “smart” camera with the capability of being installed virtually.

E2V Technologies, a UK-based firm, specializes in image sensors and microprocessors. A few years back, it was acquired by Teledyne, whose focus is on machine vision. Again, this merger brings together two complementary knowledge bases, and the expectation is that it will yield a more cost-effective machine vision system.

Software costs have also been driven down in recent years, especially as AI and Deep Learning have gained traction. Notably, one of the leading players in AI training solutions, NVIDIA, has moved into the market for AI inferencing, which is expected to have a lead to more effective, integrated analytics and improvements in machine vision architectures.

Final thoughts

Machine vision systems seem poised to continue to grow dramatically in the years to come. The widespread adoption of AI and automation has created the right infrastructure to support this trend into the near future – especially as technological advances will only increase demand for this kind of tool.

Briefly, some of the most exciting trends in the area of machine vision include the adoption of embedded vision and 3D imaging. Embedded vision is an emerging technology which integrates the camera and the processing board; this eliminates the need for a  cumbersome PC and makes the machine vision system quicker and more intuitive to work with. 3D imaging is a more established technology, but it has the capability to transform machine vision tools, creating images more quickly and with greater accuracy than has been previously seen. Together, these and other technologies are elevating Machine Vision to new heights, which can be expected to create an ever-larger demand for the tool.

 

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