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On-line and off-line signature verification using relative slope algorithm

机译:使用相对斜率算法在线和离线签名验证

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The paper presents a novel relative slope based algorithm for an on-line and off-line signature verification system capable of effectively establishing an individual's identify based solely on their handwriting characteristics. Current technologies in signature verification systems use various algorithms for feature point extraction, regression approach, Markov method, split and merge and genetic algorithms. We propose a slope based model, in which the input signature is divided into many segments using an optimized HMM method; then, the slope of every segment is calculated with respect to its previous segment, obtained after normalization of the signature. This feature of each segment is stored along with the two tier time metric information, which ensures lesser overhead with better performance while processing.
机译:本文提出了一种新颖的基于斜率基于斜率的基于斜率的基于线和离线签名验证系统,能够完全基于其手写特性建立个人识别。签名验证系统中的当前技术使用各种算法进行特征点提取,回归方法,马尔可夫方法,分裂和合并和遗传算法。我们提出了一个基于斜率的模型,其中输入签名分为许多段使用优化的HMM方法;然后,对其先前的段计算每个段的斜率,在签名的标准化之后获得。每个段的该特征与两个层次的时间公制信息一起存储,这确保了在处理时具有更好性能的开销。

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