Hand Gesture Recognition for Human-Computer Interaction Using Moment Invariants and Neural Network Classifier

Gesture recognition is of utmost importance in intelligent human-computer interaction HCI. In this paper, an algorithm using moment invariants and BP neural network classifier for hand gesture recognition is proposed. Seveni¾?invariant moments are extracted after the image segmentation, which quantitatively describes the targeted hand gesture, and then the trained BP neural networks are applied to recognize the gesture. The algorithm is validated and achieves a high recognition rate of 99% in experiments, which makes it feasible for practical HCI in some restricted environments.

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