Hand Gesture Recognition System using Radial Basis Function Neural Networks

Gestures are an important aspect of human interaction, both interpersonally and in the context of man-machine interfaces. Communication between robot and electronic devices are facing many difficulties and error level is high. So, implementation of FPGA based gesture recognition is the solution to the above mentioned problem which still limit the majority of input to keyboard and mouse. It focuses on hand gesture recognition system for controlling the hardware appliances which is highly suitable for control of equipments at home, by the handicapped people. It was implemented on Field Programmable Gate array with a radial basis function network. The radial basis function network is a 3 layer network and trained with a radial basis function algorithm to identify the classes. The system is design to identify 24 American sign-language hand signs and also real time hand gesture signs.