AN APPRAISAL OF AUTOMATED HAND GESTURE RECOGNITION TECHNIQUES

Abstract

Hand gesture segmentation for identification and prediction analysis has been a
prevalent topic in the community of the researchers working in the field of image processing and
computer vision. Hand gestures were used by humans to signify various expressions, moods and
actions. The advent of intelligent devices has made hand gesture recognition even more interesting.
Many researchers have worked on intelligent interfaces that use hand gestures for its operations.
Various state of art techniques used for hand gesture recognition has been critically analyzed. A
method using Hahn moments and neural networks has been proposed. A subsequent comparative study
has been drawn in terms of performance of the proposed and other competitive techniques. It was
observed that the proposed technique was quite accurate and efficient.