On-line handwritten signature verification using wavelets and back-propagation neural networks

被引：30

作者：

Lejtman, DZ ^{[1
]}

George, SE ^{[1
]}

机构：

[1] Univ S Australia, Sch Comp & Informat Sci, Adelaide, SA 5001, Australia

来源：

SIXTH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION, PROCEEDINGS | 2001年

关键词：

dynamic signature verification; on-line signature verification; handwritten signature verification; neural networks; wavelet transform; pattern recognition;

D O I：

10.1109/ICDAR.2001.953934

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 [模式识别与智能系统]; 0812 [计算机科学与技术]; 0835 [软件工程]; 1405 [智能科学与技术];

摘要：

This paper investigates dynamic handwritten signature verification (HSV) using the wavelet transform with verification by the backpropagation neural network (NN). It is yet another avenue in the approach to HS V that is found to produce excellent results when compared with other methods of dynamic, or on-line, HSV. Using a database of dynamic signatures collected from 41 Chinese writers and 7 from Latin script we extract features (including pen pressure, x and y velocity, angle of pen movement and angular velocity) from the signature and apply the Daubechies-6 wavelet transform using coefficients as input to a NN which learns to verify signatures with a False Rejection Rate (FRR) of 0.0% and False Acceptance Rate (FAR) less of than 0.1%.

引用

页码：992 / 996

页数：3