Image Processing and Recognition of Multiple Static Hand Gestures for Human-Computer Interaction

The use of hand gestures provides an attractive alternative to cumbersome interface devices for human-computer interaction (HCI). However, the number of hand gestures has not been fully explored for HCI application. It is necessary to achieve more gestures as the command of interface. This paper proposed a method to recognize nine different hand gestures. Using camera to get images of people wearing pink gloves, and then preprocess those images by color splitting, morphological processing and edge extraction. Fourier descriptor, edge histogram and boundary moment invariants are three methods of feature extraction. At last, the template matching was used to realize the hand gesture recognition. The average recognition rate of the nine different gestures employing three different methods is 0.859.