| 基于小波熵的低误报率人体热释电红外信号识别 |
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| 引用本文： | 王林泓,龚卫国,刘晓营,梁光清,贺莉芳.基于小波熵的低误报率人体热释电红外信号识别[J].仪器仪表学报,2009,30(12). |
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| 作者姓名： | 王林泓 龚卫国 刘晓营 梁光清 贺莉芳 |
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| 作者单位： | 重庆大学光电技术及系统教育部重点实验室,重庆,400044 |
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| 基金项目： | 国家863高技术研究发展计划，国家"十一五"基础科研基金，重庆市科技攻关计划 |
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| 摘 要： | 提出一种基于双密度双树复小波变换小波熵特征的热释电红外(PIR)信号人体识别方法.首先对人体和狗的PIR探测器输出信号进行去噪预处理,然后提取信号的双密度双树复小波变换的小波熵作为特征,最后采用最小二乘支持向量机对特征进行分类.实验结果表明:所提取的特征及分类方法对人体与狗的热释电红外信号的识别率可达93.6%.因此该识别方法能大大降低PIR探测器的误报率,并可进一步提升PIR探测器在安防和智能家居系统中应用.
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| 关 键 词： | 热释电红外探测器 双密度双树复小波变换 小波熵 最小二乘支持向量机 |
Low false alarm rate human body recognition using pyroelectric infrared signal and wavelet entropy |
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| Wang Linhong,Gong Weiguo,Liu Xiaoying,Liang Guangqing,He Lifang.Low false alarm rate human body recognition using pyroelectric infrared signal and wavelet entropy[J].Chinese Journal of Scientific Instrument,2009,30(12). |
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| Authors: | Wang Linhong Gong Weiguo Liu Xiaoying Liang Guangqing He Lifang |
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| Abstract: | A method for human body recognition using pyroelectric infrared (PIR) signal based on wavelet en-tropy (WE) of double-density dual-tree complex wavelet transform (DD-DT CWT) is proposed in the paper. The valid data is obtained by removing noise from original signal and then the wavelet entropy of DD-DT CWT is calculated. Least square support vector machine (LS-SVM) classifier is adopted to classify the feature vectors.Experiment results show that the proposed method has good ability to recognize human body and dog and the recognition rate is up to 93.6%. Therefore, the presented method can highly decrease false alarm rate and improve the application area of PIR detectors in security system and smart home system. |
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| Keywords: | pyroelectric infrared (PIR) detector double-density dual-tree complex wavelet transform (DD-DT CWT) wavelet entropy (WE) least square support vector machine (LS-SVM) |
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