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Now states have quality photo machines and rules that prohibit drivers from smiling during the snapshot to improve the accuracy of computer comparisons. North Carolina's lab scans an image and, within 10 seconds, compares the likeness with other photos based on an algorithm of factors such as the width of a chin or the structure of cheekbones. The search returns several hundred photos ranked by the similarities. "We'll get some close hits, and we'll get some hits that are right on," said Stephen Lamm, who oversees the DMV lab. The technology allowed the DMV to quickly highlight 28 different photos of one man who was apparently using many identities. It also identified one person who, as part of a sex change, came in with plucked eyebrows, long flowing hair and a new name
-- but the same radiant smile. The system is not always right. Investigators used one DMV photo of an Associated Press reporter to search for a second DMV photo, but the system first returned dozens of other people, including a North Carolina terrorism suspect who had some similar facial features. The images from the reporter and terror suspect scored a likeness of 72 percent, below the mid-80s that officials consider a solid hit. Facial-recognition experts believe the technology has improved drastically since 2002, when extremely high failure rates led authorities to scrap a program planned for the entrances to the Winter Olympics in Salt Lake City. Lamm said investigators reviewing the galleries can almost always find the right photo, using a combination of the computer and the naked eye. Marc Rotenberg, executive director of the Electronic Privacy Information Center, questioned whether the facial-recognition systems that were pushed after the Sept. 11 attacks are accurate or even worthwhile. "We don't have good photos of terrorists," Rotenberg said. "Most of the facial-recognition systems today are built on state DMV records because that's where the good photos are. It's not where the terrorists are."
[Associated
Press;
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