BIO-key issued U.S. patent for improving small fingerprint sensors
BIO-key has been granted US Patent #9,646,146 for the “Utilization of Biometric Data”, enabling BIO-key and its licensees to use existing small area fingerprint sensors to capture significantly more surface area.
The method leads to greater accuracy when performing a match, which in turn leads to better end user experiences and higher security fingerprint authentication scenarios using small area sensors.
The technology will allow device manufacturers, application creators, enterprises and end users to instill greater trust in the security of smaller fingerprint scanners.
Small area sensors capture only partial fingerprints, which affects the reliability of biometric matching as well as prevents interoperable matching between small sensors and full size sensors.
A small area sensor may be used as a touch sensor for basic on-device authentication, but emerging security issues diminish trust in small sensors for scenarios that require higher security.
The patented method resolves the area limitations of small sensors by enabling the capture of more data using the existing small sensor as a dynamic area capture device when required.
In addition, BIO-key’s flexible and interoperable capabilities enables customers to choose between matching on-device or in the cloud, and ensures interoperably across a range of sensor devices.
“Nearly every device manufacturer is including fingerprint biometric authentication as a security and convenience option for their customers,” said Mira LaCous, chief technology officer at BIO-key. “Before BIO-key’s innovation, they had to make difficult tradeoffs between sensor area footprint and accuracy. This patent and BIO-key’s IP behind it is intended to deliver the best of both worlds – enterprise-level security via sensor sizes that are unobtrusive and aesthetically pleasing.”
Earlier this month, BIO-key International issued its financial results for Q1 2017, which saw the company’s total revenues increase 229 percent to $1.4 million compared to $0.4 million in Q1 2016.