On-line signature recognition based on VQ-DTW
On-line signature recognition based on VQ-DTW
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DOI：
10.1016/j.patcog.2006.06.007
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发表时间：
2007-03-01
影响因子：
8
通讯作者：
Faundez-Zanuy, Marcos
中科院分区：
文献类型：
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作者：
Faundez-Zanuy, Marcos
本文研究了几种用于在线签名识别的模式识别算法：矢量量化（VQ）、最近邻（NN）、动态时间规整（DTW）和隐马尔可夫模型（HMM）。我们使用了330个用户的数据库，其中包括由五个不同的冒名顶替者执行的25个熟练的伪造。实验结果表明，我们提出的VQ和DTW的组合（通过得分融合）优于其他算法（DTW，HMM），并实现了最小检测成本函数（DCF）值等于1.37%的随机forests和5.42%熟练forests。此外，我们提出了另一种组合DTW-VQ方案，它可以提高远程认证系统的隐私性，避免提交整个原始动态签名信息（使用码字，而不是特征向量）。该系统实现了类似的性能比DTW。(c)2006模式识别学会。由爱思唯尔有限公司出版。保留所有权利。
This paper studies some pattern recognition algorithms for on-line signature recognition: vector quantization (VQ), nearest neighbor (NN), dynamic time warping (DTW) and hidden Markov models (HMM). We have used a database of 330 users which includes 25 skilled forgeries performed by five different impostors. This database is larger than the typical ones found in the literature.Experimental results reveal that our first proposed combination of VQ and DTW (by means of score fusion) outperforms the other algorithms (DTW, HMM) and achieves a minimum detection cost function (DCF) value equal to 1.37% for random forgeries and 5.42% for skilled forgeries. In addition, we present another combined DTW-VQ scheme which enables improvement of privacy for remote authentication systems, avoiding the submission of the whole original dynamical signature information (using codewords, instead of feature vectors). This system achieves similar performance than DTW. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.