Researchers at the Michigan State University in the US said once in use, the implications of their programme would be huge.
The research, published in the journal IEEE Transactions on Pattern Analysis and Machine Intelligence, was led by Anil Jain, a MSU professor of computer science and engineering.
Researcher Brendan Klare, a doctoral student at MSU, said: "We're dealing with the worst of the worst here.
"Police sketch 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, "often the facial sketch is not an accurate depiction of what the person looks like," Klare said.
There also are few commercial software programs available
that produce sketches based on a witness' description.
Those programmes, however, tend to be less accurate than sketches drawn by a trained forensic 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 promising.
"We improved significantly on one of the top commercial face-recognition systems," Klare said.
"Using a database of more than 10,000 mug shot photos, 45 per cent of the time we had the correct person."
All of the sketches used were from real crimes where the criminal was later identified.
"We don't match them pixel by pixel," said Prof Jain, who is also the 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 structural distribution and the shape of the eyes, nose and chin."
The MSU team plans to field test the system in about a year.