The human eye possesses 130 million light-sensitive rods and cones that convert light into chemical impulses, which travel at a rate of a billion signals per second to the brain.

Yet for all its complexity and acuity, the human eye is highly unreliable -- especially when it comes to repetitive work, such as counting the number of sesame seeds on a hamburger bun for hours at a time.

Those tasks have instead been handed over to robot and vision systems, which have grown more sophisticated, easier to use and more affordable, reaching a broader range of operations.

Vision-guided systems are not a new technology. Machine vision first appeared in the early stages of computer development in the late 1950s and 1960s, as researchers at the Massachusetts Institute of Technology, Carnegie Mellon University and Stanford University focused on the idea of artificial intelligence -- somehow using a computer to visualize and interact with its environment. Their first widespread application came 25 years ago in the semiconductor industry.

What's changing now, says Jon Keating, product marketing manager at Cognex, a manufacturer of vision systems, is their expanded use in factory automation.

"It really wasn't the technology that was limiting [vision-guided systems] early on, it was the integration," says Keating. "The intercommunication between the robot and the vision system has improved dramatically."

Cognex's In-Sight 5000 Series is mounted in a fixed position, used to accurately locate wheel hubs in an automotive application.

A vision system uses algorithms to recognize what is in an image and then locates however many objects that the robot is trained to find. An image is based on pixel-based data. Each pixel in the series has a gray-scale value, and the algorithm analyzes that data.

Robots can determine where an image was taken, so they can identify where an object is sitting and then make judgments about its size, type and quality compliance.

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