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There is a great need for alternative human-machine interfaces in several application areas. In the current paper we present the first stage of a hand gesture recognition system with the primary purpose of replacing classical input peripherals like the mouse and the keyboard. The system works by visual input and the processing has been implemented on the cellular neural/nonlinear network paradigm based Bi-i visual processing architecture. Its properties, most notably the real-time performance, allows it to be used for security, military, medical, surgery and public media applications as well.