Development of an Efficient Hand Gesture Recognition system for human computer interaction (International Journal of Engineering and Computer Science, 2015)
Human computer interaction technique has become a bottleneck in the effective utilization of the available information. The development of user interfaces influences the change in the human computer interaction (HCI). Dynamic hand posture recognition is one of the difficult tasks due to its complex background. The proposed method is implemented for hand postures taken in the natural environment. Challenges such as change of illumination and similar background are taken into consideration. Working system is based on two steps, namely hand detection and hand gesture recognition. In the hand detection process, normalized colour space skin locus is used to threshold the skin pixels from its varying background. Morphological filtering and canny edge detection is used efficaciously for removing object noise and obtain counter edges of hand gestures. Normalized cross correlation is used for pixel-wise comparison between the input image and the depository images and the best matching is considered as region of interest.