Feature Extraction for Hand Gesture Recognition : A Review [ ]

Body language is an important way of communication among humans, adding emphasis to voice messages or even being a complete message by itself. Human hand has remained a popular choice to convey information in situations where other forms like speech cannot be used. Hand gestures which can represent ideas using unique shapes and finger orientation have a scope for human machine interaction. Gesture recognition can be seen as a way for computers to begin to understand human body language, thus building a richer bridge between machines and humans than primitive text user interfaces or even GUIs (graphical user interfaces), which still limit the majority of input to keyboard and mouse. The performance of a general recognition system first depends on getting efficient features to represent pattern characteristics. There are several methods of representing such gesture trajectory feature. The aim of this paper is to show different features for hand’s image used with different approaches that yielding arobust and reliable hand gesture recognition.