How Vision Integrators are Staying Ahead of Machine Vision and Embedded Vision Design Trends

The machine vision has changed dramatically since its early years. Vision systems and components are constantly evolving into better versions of themselves while competition drives down the prices of advanced vision systems. Today, integrators can choose from a plethora of vision components to build advanced systems for manufacturers.

But even today, the evolution of machine vision technology has not stopped – if anything, it’s accelerating and integrators need to stay ahead of the latest design trends in machine vision and embedded vision. While this is not always easy, there are several ways that integrators are pushing machine vision technology into the future.

The Rise of Smart Cameras for Machine Vision

Smart cameras are a type of embedded vision technology that incorporates the image capture and processing responsibilities into one system. They are typically used for 2D imaging applications and are often a compact, low-cost solution for manufacturers that don’t need a highly advanced vision system.

One of the primary drivers of innovation for integrators is the fact that it’s become hard to improve upon smart cameras for simple vision applications. The plug and play functionality, combined with the low cost, make smart cameras ideal for a lot of end users. The rise of smart cameras have caused integrators to set their sights elsewhere, pushing the boundaries of what’s possible in vision applications as the need for integration in simple, 2D applications is decreasing.

New Frontiers in Machine Vision and Embedded Vision Design

3D vision will be a focus for innovation in the near future. Today’s 3D vision solutions can handle much of the market’s needs, however, there are areas that need improvement. For example, 3D systems require extensive development work, and there’s currently a large gap in the development tool chain.

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Artificial intelligence is an emerging technology with incredible potential for vision applications, but it’s limited in its use today. Deep learning algorithms will be an important point of innovation in the near future, allowing for entirely new applications in machine vision. At the same time, integrators will be working towards better connection between embedded vision systems and cloud computing systems for detailed data collection to inform more advanced deep learning algorithms.

3D vision, artificial intelligence, and more connected embedded systems will be some of the primary ways that vision integrators help push vision technology into the future.

As machine vision and embedded vision technology advances, integrators are constantly tasked with not only keeping up, but staying ahead of the latest design trends. While the sources of innovation mentioned above are important, they are far from the only exciting things on the horizon.