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警用面部素描法将得以改进

2026-10-16 来源:未知 作者:admin

The long-time practice of using police facial sketches2 to nab(捉住,逮捕) criminals has been, at best, an inexact art. But the process may soon be a little more exact thanks to the work of some Michigan State University researchers. A team led by MSU University Distinguished3 Professor of Computer Science and Engineering Anil Jain and doctoral student Brendan Klare has developed a set of algorithms(算法) and created software that will automatically match hand-drawn4 facial sketches to mug shots that are stored in law enforcement databases.

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Once in use, Klare said, the implications are huge. #

"We're dealing5 with the worst of the worst here," he said. "Police sketch1 artists aren't called in because someone stole a pack of gum. A lot of time is spent generating these facial sketches so it only makes sense that they are matched with the available technology to catch these criminals." #

Typically, artists' sketches are drawn by artists from information obtained from a witness. Unfortunately, Klare said, "often the facial sketch is not an accurate depiction6 of what the person looks like." #

There also are few commercial software programs available that produce sketches based on a witness' description. Those programs, however, tend to be less accurate than sketches drawn by a trained forensic7(法院的) artist. #

The MSU project is being conducted in the Pattern Recognition and Image Processing lab in the Department of Computer Science and Engineering. It is the first large-scale experiment matching operational forensic sketches with photographs and, so far, results have been promising8.

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"We improved significantly on one of the top commercial face-recognition systems," Klare said. "Using a database of more than 10,000 mug shot(面部照片) photos, 45 percent of the time we had the correct person." #

All of the sketches used were from real crimes where the criminal was later identified.

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"We don't match them pixel by pixel," said Jain, director of the PRIP lab. "We match them up by finding high-level features from both the sketch and the photo; features such as the structural9 distribution and the shape of the eyes, nose and chin."

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This project and its results appear in the March 2011 issue of the journal IEEE Transactions(处理,会报) on Pattern Analysis and Machine Intelligence.

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The MSU team plans to field test the system in about a year.

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