Design of hand gesture recognition system for human-computer interaction

Human-Computer interaction (HCI) with gesture recognition is designed to recognize a number of meaningful human expressions, and has become a valuable and intuitive computer input technique. Hand gestures are one of the most intuitive and common forms of communication, and can communicate a wide range of meaning. Vision-based hand gesture recognition has received a significant amount of research attention in recent years. However, the field still presents a number of challenges for researchers. In the vision-based hand gesture interaction process between humans and computers, gesture interpretation must be performed quickly and with high accuracy. In this paper, a low-cost HCI system with hand gesture recognition is proposed. This system uses several vision techniques. Skin and motion detection is used for capturing the region-of-interest from the background regions. A connected component labeling algorithm is proposed to identify the centroid of an object. To identify the exact area of hand gesture, the arm area is removed with the aid of a convex hull algorithm. Moreover, a real-time demonstration system is developed, based on a single-camera mechanism which allows for the use of wearable devices. Simulation results show that the recognition rate is still high, although some interference is encountered in the simulated environments.