A Robust Hand Gesture Recognition Using Combined Moment Invariants in Hand Shape

摘要

In this paper, we suggest a method that recognizes hand gesture based on moment features in hand shape. First of all, hand regions are segmented from input streams based on skin color detection. Hand detection can be achieved more easily if smart devices such as Kinect are used but we used web camera as an input device. Because hand and also face can be segmented from a frame, we try to remove face from the segmented result. From segmented hand regions palm region is extracted by removing wrist and then moment invariants are calculated from the palm region. Finally we use artificial neural network to classify the classes of the hand gestures. We perform recognition test for input patters with trained DB of 7 classes that contains hand gesture of rock-paper-scissors game and 3 different kinds of hand shape concerned with robot control.