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首页> 外文期刊>Arabian Journal for Science and Engineering >A Novel Intra-Class Distance-Based Signature Identification Algorithm Using Weighted Gabor Features and Dynamic Characteristics
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A Novel Intra-Class Distance-Based Signature Identification Algorithm Using Weighted Gabor Features and Dynamic Characteristics

机译：基于加权Gabor特征和动态特征的基于类内距离的新型特征识别算法

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摘要

Biometric recognition systems have important roles in everyday activities. Online signature verification is one of the effective biometric solutions. Due to using dynamic characteristics of the online signature, it is more robust to copy problems. This paper presents a novel intra-class distance-based signature identification algorithm based on the combination of pressure and position features of an individual's signature. In this algorithm, the pressure feature is combined with the position feature as a weight of the signature image that is called weighted signature image. By utilizing the Gabor filter on the weighted signature images, local features are extracted using a blocking scheme. Then, a distance-based strategy is employed for the signature identification process. In this strategy, the optimum decision boundary of the distance measure is selected based on the genuine and imposter intra-class distance density distribution functions. The proposed algorithm is evaluated on an SVC 2004 database containing 1,600 signatures from 40 different users. The obtained results show the effectiveness and efficiency of our algorithm in comparison with other common approaches.
机译：生物识别系统在日常活动中具有重要作用。在线签名验证是有效的生物识别解决方案之一。由于使用了在线签名的动态特性，因此复制问题更加健壮。本文提出了一种新的基于类内距离的签名识别算法，该算法基于个人签名的压力和位置特征的组合。在该算法中，压力特征与位置特征相结合，作为签名图像的权重，称为加权签名图像。通过在加权的签名图像上使用Gabor滤波器，可以使用分块方案提取局部特征。然后，将基于距离的策略用于签名识别过程。在该策略中，基于真实的和冒名顶替的类内距离密度分布函数选择距离度量的最佳决策边界。该算法在SVC 2004数据库中进行了评估，该数据库包含来自40个不同用户的1600个签名。获得的结果表明，与其他常用方法相比，我们的算法是有效的。

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