On-line signature verification based on Gabor features

Xue Ling, Yunhong Wang, Zhaoxiang Zhang, Yiding Wang
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引用次数: 15

Abstract

In this paper, the local features obtained from the signature has been used to create the texture image based on the spatio-temporal correlation matrix. The Gabor wavelets exhibit desirable characteristics of spatial locality and orientation selectivity, and are optimally localized in the space and frequency domains. So it has been chosen to extract the Gabor features of the image. Signature is a small sample point problem and Support vector machine (SVM) is especially fit for two classes' problem of small sample. The Gabor features vector has been imported to the SVM classifier and the classification result is obtained. The methods proposed in this paper are validated on the SVC 2004 database and inspiring results are obtained.
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基于Gabor特征的在线签名验证
在本文中,利用从签名中获得的局部特征来创建基于时空相关矩阵的纹理图像。Gabor小波具有良好的空间局域性和定向选择性,在空间域和频域具有最佳的局域性。因此选择对图像的Gabor特征进行提取。签名是一个小样本点问题,支持向量机特别适合于两类小样本点问题。将Gabor特征向量导入到SVM分类器中,得到分类结果。本文提出的方法在SVC 2004数据库上进行了验证,得到了令人鼓舞的结果。
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