User generic model for writer verification using multiband image scanner
User generic model for writer verification using multiband image scanner
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DOI：
10.1109/ths.2013.6699033
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发表时间：
2013-11
期刊：
影响因子：
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通讯作者：
Manabu Okawa;K. Yoshida
中科院分区：
文献类型：
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作者：
Manabu Okawa;K. Yoshida
作者身份验证在生物特征识别和取证领域有着重要的作用。手写签名在各种网络应用中的常见使用，例如通过数字终端通过手写进行信用卡认证，增加了对自动写入者验证方法的需求。然而，与人类相比，这种方法进行的性能仍然有改进的空间。由于这些应用有时会导致严重的后果，因此需要进一步的研究来提高自动写入者验证的性能。尤其是由于样品有限所带来的问题亟待解决。在实践中，每个作者的足够数量的参考文献通常是不可用的。在本文中，我们将报告用户通用模型在这种情况下的优势。对54名志愿者的实验结果表明，该方法的错误率从10.0%下降到4.6%。
Writer verification plays an important role in biometrics and forensics area. The familiar use of handwritten signatures in various network applications, e.g., credit card authentication by handwriting through digital terminal, increases the needs for the automated writer verification methods. However, there is still room for improvement in the performance conducted by such methods compared to human beings. Since the applications sometimes result in grave consequences, further research to improve the performance of automated writer verification is required. Especially, problems caused by the limited samples have to be solved. In practice, a sufficient number of references per writer are often unavailable. In this paper, we will report the advantage of the user generic model with pen pressure information in such situations. The experimental results which use samples from 54 volunteers show the decrease of error rate from 10.0% to 4.6%.