High bandwidth is essential when transmitting big data volumes in image processing systems. However, available interface technologies like GigE or CoaXPress are the bottleneck when talking about bandwidth. By pre-processing the image in the camera and applying data compression technologies this bottleneck can be mitigated.
When you are setting up a machine vision system, your choice of camera will depend on the objects that you want to inspect, the necessary speed, lighting and temperature, and available space. And not to forget—the system costs.
The term machine vision refers to the ability of machines to visually perceive their environment. A typical setting consists of a camera for capturing the images, a cable which links the camera to a PC, and the PC which does the image processing.
Video interfaces and cabling have played a significant role in bringing new capabilities to machine vision and supporting automation’s migration into a broadening range of markets.
Advances in camera, sensor, and video interface technologies have helped power the continuing development of machine vision solutions for manufacturing and quality inspection that far surpass the abilities of any human.
3-D imaging is integral to machine vision, dating back to 1960 when Larry Roberts wrote his PhD thesis at MIT on the possibility of extracting 3-D geometric information from the standard 2-D views.
Technology development moves at a dizzying pace. Check the newswire, and you’ll find a list of new products that leapfrog what was heralded as the “latest and greatest” just months ago.
ALTHOUGH THE VIDEO INTERFACE IS A SMALL PART OF THE OVERALL VISION SYSTEM, IT HAS A LARGE IMPACT ON THE USABILITY, COST AND SCALABILITY OF THE FINAL PRODUCT.
Cameras are everywhere. The need for increased automation, higher quality manufacturing, and smarter machines has fueled the growth of vision being embedded into machines, robots and other systems that can use visual data to gain a more complete understanding of the environment around them.