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红外图像中基于多特征提取的跌倒检测算法研究

Fall Detection Algorithm Based on Multi Feature Extraction in Infrared Image

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摘要

研究表明跌倒是我国老年人伤害的主要原因,而且超过一半的跌倒发生在家中。如果我们能及时发现老人跌倒并进行有效处理,就会降低跌倒对老人的伤害。因此为了检测老年人室内跌倒行为,本文从低分辨率的红外图像中,提取出4 种对跌倒敏感的特征,同时使用K 近邻算法进行分类来判断是否发生跌倒。另外,本文还设计了一套基于该算法的老年人跌倒检测系统,它具有保护隐私、准确度高、安装方便的优点。最后通过实验测试表明该跌倒检测算法的准确率高达91.25%。

Abstract

Falling is reported to be the major cause of injury in the elderly population in China. More than half of the falls this population experienced occurred at home. If we can get timely messages during the event of a fall, and process these effectively, we can reduce the potential for harm. Therefore, in order to detect indoor falls of the elderly, this study extracts four fall-sensitive features in low-resolution infrared images, after which the k-nearest neighbor algorithm is used to determine whether a fall has occurred or not. Moreover, this paper also designs a complete fall detection system for the elderly based on the proposed algorithm, which offers the advantages of privacy protection, high accuracy, and convenient assembly. Results of experiments show that the accuracy of the fall detection system is as high as 91.25%.

Newport宣传-MKS新实验室计划
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中图分类号:TP391.4

所属栏目:图像处理与仿真

基金项目:江苏省科技支撑计划项目(BE2014639);中国科学院科技服务网络计划(KFJ-STS-SCYD-007);苏州市科技计划项目(SYS201664)。

收稿日期:2017-05-15

修改稿日期:2017-06-23

网络出版日期:--

作者单位    点击查看

杨任兵:上海大学通信与信息工程学院,上海 200444
程文播:中国科学院苏州生物医学工程技术研究所,江苏 苏州 215163
钱庆:中国科学院苏州生物医学工程技术研究所,江苏 苏州 215163
章强:中国科学院苏州生物医学工程技术研究所,江苏 苏州 215163
钱俊:中国科学院苏州生物医学工程技术研究所,江苏 苏州 215163
潘宇骏:中国科学院苏州生物医学工程技术研究所,江苏 苏州 215163

联系人作者:杨任兵(yangrenbing2014@163.com)

备注:杨任兵(1993-),男,硕士研究生,研究方向:光电信号和生物医学信号处理

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引用该论文

YANG Renbing,CHENG Wenbo,QIAN Qing,ZHANG Qiang,QIAN Jun,PAN Yujun. Fall Detection Algorithm Based on Multi Feature Extraction in Infrared Image[J]. Infrared Technology, 2017, 39(12): 1131-1138

杨任兵,程文播,钱庆,章强,钱俊,潘宇骏. 红外图像中基于多特征提取的跌倒检测算法研究[J]. 红外技术, 2017, 39(12): 1131-1138

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