基于HMM与D-S证据理论的手势身份认证方法

Gesture Authentication Method Based on HMM and D-S Evidence Theory

文章针对智能手机用户个人隐私及信息面临的安全问题,提出了一种基于HMM和D-S证据理论的手势身份认证方法。首先通过智能手机触摸屏传感器采集手势运动轨迹的原始数据并进行预处理,提取手势特征序列作为HMM的观察序列,建立合法用户手势模型;然后将测试手势特征序列与手势模型进行匹配计算获取初步判断结果 ;最后采用D-S证据理论组合规则得到融合后的概率分配函数进行最终的认证决策。仿真实验表明,文中方法与其他方法相比可有效提高手势身份认证的精度。

Aiming at the security problems of smart phone users＇ privacy and information, a gesture recognition identity authentication method based on HMM and D-S evidence theory is adopted. Firstly, the original data of the gesture trajectory is collected by the touch screen sensor of the smart phone, the gesture feature sequence is preprocessed and extracted as the observation sequence of the HMM, and a legal user gesture model is established. Secondly, the preliminary judgment result is obtained by matching the test gesture feature sequence and the gesture model, and then use D-S evidence theory combination rules to get the fusion probability distribution function for the final certification decision. Simulation results show that compared with other methods, this method can effectively improve the accuracy of gesture recognition authentication.