Researchers discovered that not all fingerprints are unique and different

Engineers from Columbia and the American University of Buffalo A A new fingerprint analysis using artificial intelligence (AI) that overturns a long-held belief in forensic medicine that no two fingerprints are ever identical on different fingers of the same person.

The discovery was reported Wednesday by the magazine Science Advances, With a reliability of 99.99%, it has shown Fingerprints from any two fingers of the same person are much more similar than previously thought.

Fingerprints are essential in crime labs and in billions of mobile phones worldwide for digital authentication, however, currently, all technologies in this area are designed under the premise that no two fingerprints are the same.

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

However, a study promoted by Gabe GuoThe Columbia engineering student, along with other researchers from the same university and the University at Buffalo, have shown that it is possible to overcome this limitation by analyzing the hitherto understudied characteristics of fingerprints.

Guo and his colleagues searched a public US government database with some 60,000 fingerprints and fed them in pairs into an artificial intelligence-based system called a deep contrast network.

Sometimes the pair was with the same person (but with different fingers) and sometimes with different people.

Engineers, without prior forensic knowledge, extracted the fingerprint from the representation vector 525,000 images Using a deep neural network and made a surprising discovery: Fingerprints of different fingers of the same person are very similar.

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

The model has been successfully tested with women of various gender and ethnic groups.

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

The researcher also emphasizes that it can be discovered Improving convenience and accessibility of digital authentication technologies.

(with information from EFE)