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Online Handwritten Signature Verification Using Neural Network Classifier Based on Principal Component Analysis
Joint Authors
Iranmanesh, Vahab
Ahmad, Sharifah Mumtazah Syed
Adnan, Wan Azizun Wan
Yussof, Salman
Arigbabu, Olasimbo Ayodeji
Malallah, Fahad Layth
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-14
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
One of the main difficulties in designing online signature verification (OSV) system is to find the most distinctive features with high discriminating capabilities for the verification, particularly, with regard to the high variability which is inherent in genuine handwritten signatures, coupled with the possibility of skilled forgeries having close resemblance to the original counterparts.
In this paper, we proposed a systematic approach to online signature verification through the use of multilayer perceptron (MLP) on a subset of principal component analysis (PCA) features.
The proposed approach illustrates a feature selection technique on the usually discarded information from PCA computation, which can be significant in attaining reduced error rates.
The experiment is performed using 4000 signature samples from SIGMA database, which yielded a false acceptance rate (FAR) of 7.4% and a false rejection rate (FRR) of 6.4%.
American Psychological Association (APA)
Iranmanesh, Vahab& Ahmad, Sharifah Mumtazah Syed& Adnan, Wan Azizun Wan& Yussof, Salman& Arigbabu, Olasimbo Ayodeji& Malallah, Fahad Layth. 2014. Online Handwritten Signature Verification Using Neural Network Classifier Based on Principal Component Analysis. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1049401
Modern Language Association (MLA)
Iranmanesh, Vahab…[et al.]. Online Handwritten Signature Verification Using Neural Network Classifier Based on Principal Component Analysis. The Scientific World Journal No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1049401
American Medical Association (AMA)
Iranmanesh, Vahab& Ahmad, Sharifah Mumtazah Syed& Adnan, Wan Azizun Wan& Yussof, Salman& Arigbabu, Olasimbo Ayodeji& Malallah, Fahad Layth. Online Handwritten Signature Verification Using Neural Network Classifier Based on Principal Component Analysis. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1049401
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049401