In the criminal justice system, the people are divided into two separate yet equally important groups: the tattooed and those who aren't inked. This is the story of a database that enables law enforcement to track the former. And while that sounds like a technology from the future, competing systems have already been developed, and were demonstrated at the Tattoo Recognition Technology Challenge Workshop recently put on by the National Institute of Standards and Technology (NIST).
According to a NIST computer scientist named Mei Ngan, the challenge was partially successful. She explained, “state-of-the-art algorithms fared quite well in detecting tattoos, finding different instances of the same tattoo from the same subject over time, and finding a small part of a tattoo within a larger tattoo.” There were aspects of the challenge that the experts' algorithms failed at, such as spotting similar (but not exactly the same) tattoos on different people and recognizing a tattoo from non-photographic sources, such as a police sketch.
The challenge brought together six organizations to see what solutions can be developed going forward, but these teams already have similar products on the market right now. Purdue University's GARI, for example, collects and analyzes gang tattoos and graffiti for an app that law enforcement can access on mobile devices. Even though the collected experts could not successfully track similar tattoos across the library of photography, MITRE (an American not-for-profit organization) has developed technology that breaks an image of a tattoo down into a subset of elements.
So while people may get their tattoos to express their individuality, these systems could recognize every mom tattoo or coverup and log them into a database that makes them trackable. Images of the tattooed could be recorded via any of the large number of cameras that we have all accepted as a part of our daily lives, such as traffic cameras or cop car dashboard cameras.
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