HAND GESTURE RECOGNITION USING CLUSTERING BASED TECHNIQUE

Abstract

Hand Gesture Recognition play vital role for developing human computer interaction and sign language recognition. Sign language recognition is used for deaf and dump people. Existing system based on vision based static hand gesture recognition. It performed static hand gesture recognition. In existing system, Contour tracking algorithm is used for feature extraction and radial basis functional neural network (RBFNN) is used for classification. RBFNN provides good classification accuracy. Existing system is limited to static hand gesture recognition. Proposed work performs Dynamic Hand Gesture Recognition using clustering based technique. Clustering based technique provides good classification accuracy. Fourier Descriptor method is used for feature extraction in the proposed method. This method will reduce time complexity and it will improve accuracy.