Hand Gesture Recognition for Deaf-Mute using Fuzzy-Neural Network

Communication is important for every individual to convey whatever information they want to people and vice-versa. Hand gesture is one of the important methods of nonverbal communication for human beings. There are plenty of methods that are used to recognize hand gestures with different accuracies and precision, some has advantages and disadvantages. The general objective of this paper is to develop a hand gesture translator gloves with the use of fuzzy-neural network to eliminate the barrier of communication for deaf-mute and non-deaf person. This paper studied the effectiveness of combining fuzzy logic and neural network for hand gesture recognition. The study is successful with the objective of combining Fuzzy Logic algorithm with Neural Networks algorithm to improve the hand gesture recognition rate compared to as an individual. With the earning capability of the Neural Network combined with the simple interpretation and implementation by means of Fuzzy Logic, it unite their advantages and exclude disadvantages like the ability of Fuzzy Logic to interpret input to output that Neural Network is unable to do. The total percent of recognition rate was met with an average of 92.58%.