How do you think the new GigE standards will influence the machine vision industry?
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By Martin Ghillemyn
Researchers and scientists are predicting a new and widespread wave of the H1N1 virus, better known as swine flu, this summer. The Centers for Disease Control and Prevention warn that nearly 2 million Americans could be hospitalized this winter, with as many as 300,000 in heavily affected regions, according to an August report by the President’s Council of Advisors on Science and Technology. (The H1N1 outbreak could be milder, the CDC says). The same warning, of course, is being issued worldwide.
This virus is most dangerous because it never has circulated among humans and isn’t related to previous or current human seasonal influenza viruses. It is spread from person-to-person and is transmitted as easily as normal seasonal flu and can be passed by exposure to infected droplets expelled by coughing or sneezing that can be inhaled or that contaminate hands or surfaces.
Obviously, this is more likely in public places, including airports, other transportation sites, sports facilities, actually wherever people gather in large numbers. A new technology—or really a new use of one—can help make a difference. Xenics (Leuven, Belgium) is offering a new automated IR thermography system to counter the spreading of dangerous respiratory diseases, including swine flu. The Xenics Raven-384 is based on a highly sensitive uncooled microbolometer IR camera. It detects, from a distance and in real time, suspicious signs of elevated body temperature in passing travellers at a sensitivity of up to 0.05°C.
The Raven-384 captures travellers’ temperature patterns as emitted from their skins and displays them as high-definition infrared images on a PC screen linked via a standard Ethernet connection. The result is a live, 384 x 288 pixel visual image of the passenger superimposed with various color contours representing crucial temperature gradients. Temperatures above a certain safety mark can be highlighted.
This specific setup of thermal imaging detects body temperatures above a given value. On the other hand, any other high-temperature occurrences outside the pre-determined range are excluded, for instance if people are carrying or consuming hot beverages like coffee. Coffee will not induce a higher body temperature, but a coffee cup in the field of view will give a false alarm.