Michael Nolte

Human perception based counterfeit detection for automated teller machines

A robust vision system for the counterfeit detection of bank ATM keyboards is presented. The approach is based on the continuous inspection of a keyboard surface by the authenticity verification of coded covert surface features. For the surface coding suitable visual patterns on the keyboard are selected while considering constraints from the visual imperceptibility, robustness and geometrical disturbances to be encountered from the aging effects. The systems robustness against varying camera-keyboard distances, lighting conditions and dirt-and-scratches effects is investigated. Finally, a demonstrator working in real-time is developed in order to publicly demonstrate the surface authentication process.