Hand gesture recognition is very significant for human-computer interaction. In this work, we present a novel real-time method for\nhand gesture recognition. In our framework, the hand region is extracted from the background with the background subtraction\nmethod. Then, the palm and fingers are segmented so as to detect and recognize the fingers. Finally, a rule classifier is applied to\npredict the labels of hand gestures. The experiments on the data set of 1300 images show that our method performs well and is\nhighly efficient. Moreover, our method shows better performance than a state-of-art method on another data set of hand gestures.
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