结合HOG和LBP特征的分类器离线签名验证

2011 International Joint Conference on Biometrics (IJCB) Pub Date : 2011-10-11 DOI:10.1109/IJCB.2011.6117473

M. Yilmaz, B. Yanikoglu, C. Tirkaz, A. Kholmatov

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引用次数: 116

摘要

提出了一种基于签名局部直方图特征的离线签名验证系统。使用笛卡尔坐标系和极坐标系统将签名划分为区域，并为每个区域计算两个不同的直方图特征:定向梯度直方图(HOG)和局部二值模式直方图(LBP)。

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Offline signature verification using classifier combination of HOG and LBP features

We present an offline signature verification system based on a signature's local histogram features. The signature is divided into zones using both the Cartesian and polar coordinate systems and two different histogram features are calculated for each zone: histogram of oriented gradients (HOG) and histogram of local binary patterns (LBP).

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2011 International Joint Conference on Biometrics (IJCB)

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