A novel dynamic gesture segmentation method is proposed by combining three-frame difference method and skin-color elliptic boundary model. Firstly, the possible dynamic gesture region is determined by extracting the target property of movement via three-frame difference method, and then the target area is gotten by skin-color detection in thepossible region using skin-color elliptic boundary model. By extracting double features of dynamic hand gestures, the proposed method can effectively solve the problem that the large area of skin-color background was mistakenly identified as hands. The area of face and bare arms are removed by setting a reasonable threshold. Furthermore, for overcoming the shortcoming of traditional three-frame difference method that cannot detect static gestures, the proposed method has been improved and shown robustness on relative static gestures. The experimental results demonstrate the efficiency for dynamic hand gestures segmentation and the proposed method is suitable for real-time systems such as dynamic gesture recognition.