Offline Signature Verification with VLAD Using Fused KAZE Features from Foreground and Background Signature Images
Offline Signature Verification with VLAD Using Fused KAZE Features from Foreground and Background Signature Images
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DOI：
10.1109/icdar.2017.198
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发表时间：
2017-11
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通讯作者：
Manabu Okawa
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文献类型：
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作者：
Manabu Okawa
离线签名验证作为一种个人身份认证工具已经被广泛接受，特别是在生物识别和取证领域。然而，自动化系统在广泛的写入条件下的性能仍然不足。最有希望的方法是考虑关于法医文件审查员(FDES)视觉信息认知加工的最新知识。为了将FDES的认知处理方法成功地应用到离线签名验证中，提出了一种基于融合KAZE特征的局部聚集描述符矢量(VLAD)的离线签名验证方法。该方法在一个流行的MCYT-75签名数据集上的实验结果如下：(1)背景签名图像和前景签名图像的KAZE特征均表现出较好的性能。(2)融合了前景和背景签名图像的KAZE特征，进一步提高了算法的性能。(3)在典型的融合方法中，表示级融合是融合KAZE特征以获得良好性能的合理选择。(4)当表示级融合产生高维VLAD向量时，对原始VLAD向量使用主成分分析可以提供维度更紧凑的向量而不会有显著的性能损失。(5)与现有的离线签名验证方法相比，该方法具有更低的错误率。
Offline signature verification has been widely accepted as a tool for individual authentication, especially in the field of biometrics and forensics. However, the performance of an automated system under a wide range of writing conditions is still inadequate. The promising approach is to consider recent knowledge about the cognitive processing of visual information of forensic document examiners (FDEs). To implement FDEs' cognitive processing method successfully into offline signature verification, specifically this study proposes a new approach based on vector of locally aggregated descriptors (VLAD) with fused KAZE features detected from foreground and background signature images with a recent fusion strategy. The experimental results by the proposed method with a popular MCYT-75 signature dataset can be summarized as follows: (1) the KAZE features from the background signature images as well as the ones from the foreground images show good performance. (2) The use of fused KAZE features from foreground and background signature images allows us to further improve of the performance. (3) Among the typical fusion methods, the representation-level fusion is a rational choice for fusing the KAZE features to obtain good performance. (4) While the representation-level fusion produces a high-dimensional VLAD vector, the use of principal component analysis for the original VLAD vector can provide a more dimensionally compact vector without significant loss in performance. (5) Finally, the proposed method provides much lower error rates than the existing state-of-the-art offline signature verification methods.