A STUDY ON HAND GESTURE RECOGNITION TECHNIQUE

Abstract

Gesture recognition is a growing field of research and among various human computer interactions; hand gesture recognition is very popular for interacting between human and machines. It is non verbal way of communication and this research area is full of innovative approaches. This project aims at recognising 40 basic hand gestures. The main features used are centroid in the hand, presence of thumb and number of peaks in the hand gesture. That is the algorithm is based on shape based features by keeping in the mind that shape of human hand is same for all human beings except in some situations. The main shape parameters are thumb and four fingers. The hand gesture of user is captured and stored in the disk. It is then converted to binary image; in this step pre-processing is performed to eliminate noise then features are extracted. On the basis of these features a five bit binary sequence is generated. In this project rule based classification is used. The algorithm is tested for 40 different hand gestures with the database of 200 images taken from a simple camera of 3.2 mega pixels.