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中文摘要：
侧重签名能量特征提取方法的研究，提出了一种基于小波分析的在线手写汉字签名验证算法。基于Daubechies小波的方法对签名波形进行分解，重构部分波形后，提取签名波形在跳变点处的能量，并对跳变点处签名能量进行大小排序，选出M个较大能量作为特征矢量，并提出了一种新的匹配算法。算法能快速消除随机伪造签名，实现自动签名验证的目的。实验表明，对于随机伪造签名，当误拒率为0％时，误纳率为8．5％。
英文摘要：
An on-line handwriting Chinese signature verification algorithm based on wavelet is proposed. By means of Daubechies wavelet decomposition of signature wave, and after reconstruction of part signal, the energy of sharp trajectory change point in the signature wave is extracted. Then, all the signature energies are arranged in descending order and the first M most dominant energies are chosen as feature vector. A new algorithm of classification is put forward. The presented algorithm based on energy feature is capable of eliminating quickly random forgeries for automatic signature verification. Experiment results show that false acceptance rate is 8.5 percent while false rejection rate is 0 percent for random forgery.
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