针对手势识别系统中的手势分割部分提出了一种改进的结合三帧差分法和肤色椭圆边界模型的动态手势分割方法。运用三帧差分法提取动态手势的运动特征，初步确定手势所在区域，然后运用肤色椭圆边界模型对该区域进行肤色判别从而确定目标。通过提取双特征，可有效解决复杂背景下大面积肤色背景被误检的问题。通过合理设置运动检测过程中的阈值，可有效去除运动幅度较小的人脸和裸露手臂部分。同时针对三帧差分法不能检测静态手势进行了改进，使提出算法对视频流中手势的短暂停留具有极强的鲁棒性。实验结果表明，提出算法能准确高效的检测出动态手势，适用于动态手势识别等实时系统中。

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.