Machines That Can See

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Machines That Can See

After more than 50 years of research, machine vision technology has recently reached the point in its development where it is ready for commercial application.  Now, the rush is on to make the most profitable use of it. 

Machine vision technology teams up specialized computer hardware, cameras, and software to create a machine that can see and recognize objects and people and then make useful interpretations of those images.  One application described recently by CNet News,1 is a system from Hyperactive Technologies that monitors operations at fast food restaurants.  That machine vision system keeps track of cars coming into the parking lot and then compares the anticipated demand to the current amount of cooked food that is available.  By calculating cooking times, it can alert the staff ahead of time as to what food items they will need to prepare next, thereby improving efficiency, as well as customer satisfaction.  The system is currently being tested at Popeye's Chicken and Jack in the Box outlets.  Zaxby's, which already has the system installed at more than 100 restaurants in its chain, says it is saving over $800,000 a year because the system wastes less food.

According to The Economist Technology Quarterly,2 these types of systems are being used to improve efficiency in the manufacture of everyday goods, such as diapers.  If a more accurate machine vision system can reduce the wasted material that is cut by even just one millimeter per diaper, it can save millions of dollars for a company that produces billions of diapers. 

Another example involves companies that sell consumer packaged foods, such as rice.  Rice sorters are using computer vision to scan four tons of rice an hour and then use air jets to eject discolored grains, rocks, or other debris.  That requires the extremely fast and accurate computer vision systems that are now becoming widely available.

Omron Corporation in Japan is developing a system that can tell if employees, such as cashiers, are smiling at customers or not.  The same sort of system can be used to determine if an expression is authentic or not.  Unilever is using it to determine how food tasters are reacting to a product.  Procter & Gamble is also using it to monitor responses of participants in focus groups to see if their words match their facial expressions.

MICTA, a media laboratory in Australia, is testing ways to use machine vision to target advertising.  A digital billboard called TABANAR, with a camera installed in it, reads a person's gender, age, and hair growth...

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