Online signature verification using neural network and pearson correlation features

Author

Iranmanesh, Vahab ; Mumtazah Syed Ahmad, Sharifah ; Wan Adnan, Wan Adilah ; Layth Malallah, Fahad ; Yussof, Salman

Author_Institution

Fac. of Eng., Univ. of Putra (UPM), Serdang, Malaysia

fYear

2013

fDate

2-4 Dec. 2013

Firstpage

18

Lastpage

21

Abstract

In this paper, we proposed a method for feature extraction in online signature verification. We first used signature coordinate points and pen pressure of all signatures, which are available in the SIGMA database. Then, Pearson correlation coefficients were selected for feature extraction. The obtained features were used in back-propagation neural network for verification. The results indicate an accuracy of 82.42%.

Keywords

backpropagation; correlation methods; database theory; feature extraction; handwriting recognition; neural nets; Pearson correlation features; SIGMA database; backpropagation neural network; feature extraction; online signature verification; pen pressure; signature coordinate points; Accuracy; Biological system modeling; Correlation; Feature extraction; Protocols; Feature Extraction; Neural Network; Online Signature Verification; Pattern Recognition; Pearson Correlation Coefficients;

fLanguage

English

Publisher

ieee

Conference_Titel

Open Systems (ICOS), 2013 IEEE Conference on

Conference_Location

Kuching

Print_ISBN

978-1-4799-3152-1

Type

conf

DOI

10.1109/ICOS.2013.6735040

Filename

6735040