Researchers found that not all fingerprints are unique and different

Engineers from the American universities of Columbia and Buffalo have created a New fingerprint analysis using artificial intelligence (AI) which overturns the long-held belief in forensic medicine that there are never two identical fingerprints, even on different fingers of the same person.

The discovery, reported this Wednesday by the magazine science advancement, It has been demonstrated with a reliability of 99.99% The fingerprints of any two fingers of the same person are more similar than ever before.

Fingerprints are essential in crime laboratories for solving cases and in billions of mobile phones around the world for digital authentication, however, for now, all technologies in this area are designed on the basis that they have no two identical fingerprints. .

To date, fingerprints are not useful in situations where the available prints are those of fingers other than those recorded, such as at a crime scene.

However, a study publicized by gab guoAn engineering student at Columbia, in collaboration with other researchers from the same university and the University at Buffalo, has shown that it is possible to overcome this limitation by analyzing hitherto unstudied characteristics of fingerprints.

Guo and his colleagues found a public US government database with some 60,000 fingerprints And entered them in pairs into an artificial intelligence-based system known as a deep contrast network.

Sometimes the pairs belonged to the same person (but with different fingers) and sometimes to different people.

Engineers, without prior forensic knowledge, extracted fingerprint representation vectors 525,000 images Using deep neural networks and made a surprising discovery: Different fingerprints of the same person are extremely similar.

They found that the orientation of the ridges near the center of the print (the most prominent area of ​​the print) explains much of this similarity, and that the pattern holds for all pairs of fingers of the same person.

The model has been successfully tested with women of different genders and racial groups.

“We hope this additional information can help us prioritize leads when there are multiple possibilities, exonerate innocent suspects, or even create new leads for unsolved cases,” Guo said in a statement from Columbia University. “

The researchers also emphasize that their discovery may be possible Improve convenience and accessibility of digital authentication technologies.

(with information from EFE)