Optical Fingerprint Recognition Could Have Applications in Bank, Internet Security

Kathleen G. Tatterson

GAITHERSBURG, Md. -- Researchers at the National Institute of Standards and Technology (NIST) have combined optical correlation methods and digital neural networks to provide more accurate real-time fingerprinting for financial, credit and Internet security applications.
In a project sponsored by the FBI's Criminal Justice Information Services, scientists at NIST's Information Technology Laboratory have explored how optical methods of 3-D holography and image storage can help a neural network recognize the unique patterns in fingerprints.
Such methods would be more accurate than unaided digital image correlation and more user-friendly than retinal scanning, in which a laser beam is shot into the subject's eye and recorded by a charge-coupled device for identification, according to Victor McCrary, project manager.

Time-consuming process
The FBI distinguishes fingerprints by comparing the coordinates of the fingertips' ridge ending. Investigators file fingerprints based on basic physical characteristics (shape, swirl, etc.). This is a time-consuming and highly inaccurate process that can result in false matches, said Charles Wilson, a scientist at NIST.
In the 30 million fingerprint samples processed to date, the optically enhanced system has not indicated a single incorrect match. Such accuracy would make a computer security system nearly impossible to fool, he said. Also, the preliminary tests show a pattern-recognition accuracy of 100 percent, virtually eliminating the possibility of mistaken denials of access, Wilson said.
In optical pattern recognition, scientists load a fingerprint image onto a liquid crystal spatial light modulator (see figure). A reference beam interferes with the resulting Fourier spectrum to record a Fourier-transform hologram into the neural network. The system can then compare the image to any new fingerprint pattern introduced.
The optical system can more accurately enter the fingerprint pat-tern into the neural network system, which in turn can "recognize" and differentiate a pattern when it is reintroduced into the system.
Some possible commercial applications include the use of fingerprint images for credit card verification, access to automatic teller machines and access to the Internet in place of or along with passwords.
The laboratory is seeking corporate collaborators to move into the project's next phase: refining the neural network and testing the prototype system in industry. NIST plans to work with the Financial Services Technology Consortium, an organization of banks, financial service providers, technology companies, national laboratories, universities and government agencies.
However, Wilson estimates that complete commercialization is still a long way off. "It won't be ready for the next generation of end users," he said. "Maybe the one after that."