A dynamic gesture recognition system for the Korean sign language (KSL)

Abstract

The sign language is a method of communication for the deaf-mute. Articulated gestures and postures of hands and fingers are commonly used for the sign language. This paper presents a system which recognizes the Korean Sign Language (KSL) and translates into a normal Korean text, A pair of Data-Gloves are used as the sensing device for detecting motions of hands and fingers. For efficient recognition of gestures and postures, a technique of efficient classification of motions is proposed and a fuzzy min-max neural network [4] is adopted for on-line pattern recognition.