Hand Gesture Recognition for Thai Sign Language in Complex Background Using Fusion of Depth and Color Video

Abstract

Hand detection and gesture recognition are the active research area in the computer vision. The main purpose to develop the sign language recognition and Human Computer Interaction (HCI). This article investigates and develops the technique to recognize hand posture of Thai sign language in a complex background using fusion of depth and color video. The new technology of sensors, such as the Microsoft Kinect, recently provides the depth video which helps researchers to find the hand position in the scene. This advantage is used to segment the hand sign in the color video without the environment interference such as skin color background. The histograms of oriented gradients are used to extract the image features of hand sign. These features are then pass to the artificial neural network for training and recognition. The result showed that the proposed method is robust to detect the hand gestures in the complex background. It provides the accuracy recognition for the Thai fingerspelling of 84.05%