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Bi-Modal Biometric Authentication by Face Recognition and Signature Verification

by Ibiyemi T.s, Ogunsakin J, Daramola S.a
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 42 - Number 20
Year of Publication: 2012
Authors: Ibiyemi T.s, Ogunsakin J, Daramola S.a
10.5120/5816-8127

Ibiyemi T.s, Ogunsakin J, Daramola S.a . Bi-Modal Biometric Authentication by Face Recognition and Signature Verification. International Journal of Computer Applications. 42, 20 ( March 2012), 17-21. DOI=10.5120/5816-8127

@article{ 10.5120/5816-8127,
author = { Ibiyemi T.s, Ogunsakin J, Daramola S.a },
title = { Bi-Modal Biometric Authentication by Face Recognition and Signature Verification },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 42 },
number = { 20 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 17-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume42/number20/5816-8127/ },
doi = { 10.5120/5816-8127 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:31:49.518566+05:30
%A Ibiyemi T.s
%A Ogunsakin J
%A Daramola S.a
%T Bi-Modal Biometric Authentication by Face Recognition and Signature Verification
%J International Journal of Computer Applications
%@ 0975-8887
%V 42
%N 20
%P 17-21
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Face and signature are still two most dominant authentication modes in banking, legal documents, or personnel records in spite availability of more robust biometric modes. Hence, it is imperative to develop low-cost and reliable automated face recognition and signature verification system. Therefore, this paper presents our work in development of a two-in-one portable low-cost dsPIC30F3013 digital signal processing microcontroller based system for real time face recognition and signature verification. The face recognition part of the system is based on eigenface method, while the offline signature verification is based on 12-dimensional feature vector derived from the signature's geometric attributes

References
  1. Ibiyemi T. S. , Aliu S. A. . (2002), "On Computation of Optimum Basis Vector for Face Detection and Recognition", Abacus: Mathematics Series, 29(2), pp 144-149
  2. Turk M. , Pentland A. , (1991), "Eigenfaces for Recognition", Journal of Cognitive Neuroscience, vol. 3, no. 1, pp71-86
  3. Brian Harding, Cat Jubinski, "A Standalone Face Recognition Access Control System", ECE4760 Final Project Report, URL: http://people. ece. edu/land/courses/ece4760
  4. Daramola S. , Ibiyemi T. S. , (2010), "Novel Feature Extraction Techniques for Offline Signature Verification", International Journal of Engineering Science and Technology, vol. 12, no. 7, pp3137-3143.
  5. Daramola S. , Ibiyemi T. S. , (2010), "Person Identification System using Static and Dynamic Signal Fusion", International Journal of Computer Science & Information Security, vol. 6, no. 7, pp88-92.
  6. Ashish Dhawan, Aditi R. Ganesan, (2004), "Handwritten Signature Verification", ECE533 Project Report
  7. Huang K. , Yan H. , (1997), "Offline Signature Verification based on Geometric Feature Extraction and Neural Network Classification", Pattern Recognition 30, pp. 9-17.
Index Terms

Computer Science
Information Sciences

Keywords

Authentication Face Recognition Signature Verification Offline Eigenface

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