Uyghur Off-line Signature Verification Based on Modified Corner Line Features

被引：0

作者：

Ubul, Kurban ^{[1
]}

Yibulayin, Tuergen ^{[1
]}

Mahpirat ^{[2
]}

机构：

[1] Xinjiang Univ, Sch Informat Sci & Engn, Urumqi 830046, Peoples R China

[2] Xinjiang Univ, Educ Berou, Urumqi 830046, Peoples R China

来源：

INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTER SCIENCE (AICS 2016) | 2016年

基金：

中国国家自然科学基金;

关键词：

Uyghur; Handwritten signature; Modified corner line features; Verification; RECOGNITION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A modified corner line features based off-line signature verification method proposed for Uyghur handwritten signature in this paper. The signature images were preprocessed according to the nature of Uyghur signature. Then 3 types of corner line features and modified corner curve features were extracted separately. Experiments were performed using Euclidean distance classifier and non-linear SVM classifier for Uyghur signature samples from 150 genuine signatures, 72 random and skilled forgeries are selected from our Uyghur handwritten signature database. Experiments indicate that the MCLF-48 with training 75 samples has obtained 2.16% of FRR and 2.27% of FAR with none-linear SVM classifier. It was concluded that modified corner line features based verification method can capture the nature of Uyghur signature and its writing style more efficiently.

引用

页码：465 / 469

页数：5

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