Biometrics and facial recognition have made border control more efficient and secure. However, some types of fraud still pose a challenge for border control officers and automated border control systems. These include so-called morphing attacks. Therefore, software algorithms that recognize facial morphs during automated border control can substantially increase border security.
Secunet has developed its own algorithm to detect morphed facial images, which has been integrated into its Easygate automated border control system. At this year’s Passenger Terminal EXPO, Secunet will show the Easygate with morphing attack detection (MAD) in action during live demonstrations. Passengers can pass through quickly and independently, enjoying a seamless travel experience, and expo visitors will be able to try this for themselves at the show.
Secunet recently submitted its algorithm to the independent, internationally recognized National Institute of Standards and Technology (NIST) Face Recognition Vendor Test (FRVT) MORPH test. The algorithm implements differential morphing attack detection, which checks a potentially morphed facial image against a second image, which is usually live-captured and therefore trusted. Secunet's algorithm achieves excellent results in the NIST FRVT MORPH test.