Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30172
Signature Recognition and Verification using Hybrid Features and Clustered Artificial Neural Network(ANN)s

Authors: Manasjyoti Bhuyan, Kandarpa Kumar Sarma, Hirendra Das

Abstract:

Signature represents an individual characteristic of a person which can be used for his / her validation. For such application proper modeling is essential. Here we propose an offline signature recognition and verification scheme which is based on extraction of several features including one hybrid set from the input signature and compare them with the already trained forms. Feature points are classified using statistical parameters like mean and variance. The scanned signature is normalized in slant using a very simple algorithm with an intention to make the system robust which is found to be very helpful. The slant correction is further aided by the use of an Artificial Neural Network (ANN). The suggested scheme discriminates between originals and forged signatures from simple and random forgeries. The primary objective is to reduce the two crucial parameters-False Acceptance Rate (FAR) and False Rejection Rate (FRR) with lesser training time with an intension to make the system dynamic using a cluster of ANNs forming a multiple classifier system.

Keywords: offline, algorithm, FAR, FRR, ANN.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1076624

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1325

References:


[1] A. Prasad: An Offline Signature Verification System., Surathkal -574157, [email protected]
[2] Y. Kato, D. Muramatsu and T. Matsumoto: "A Sequential Monte Carlo Algorithm for Adaptation to Intersession Variability in On-line Signature Verification", Department of Electrical Engineering and Bioscience, Waseda University, 3-4-1 Okubo, Shinjuku, Tokyo 169-8555, Japan,
[3] D. Jena, B. Majhi and S. K. Jena: "Improved Offline Signature Verification Scheme Using Feature Point Extraction Method" , National Institute of Technology Rourkela, Orissa, India, Journal of Computer Science 4 (2): 111-116, 2008 ISSN 1549-3636 2008 Science Publications
[4] T. E. Emrezgndz and M. E. Karslgil: "OffLine Signature Verification And Recognition By Support Vector Machine", Computer Engineering Department, Yldz Technical University Yldz , Istanbul, Turkey,
[5] A. T. Wilson: "Offline Handwriting Recognition Using Articial Neural Networks", University of Minnesota, Morris Morris.,
[6] C. B. Owen and F. Makedon: High Quality Alias Free Image Rotation, Proceedings of 30th Asilomar Conference on Signals, Systems, and Computers Pacific Grove, California, November 2-6, 1996.
[7] I. S. I. Abuhaiba: "Offine Signature Verication Using Graph Matching", Department of Electrical and Computer Engineering, Islamic University of Gaza,
[8] Mathworks: "Inc. Matlab Toolbox", http://www.mathworks.com,
[9] S. Haykin, Neural Networks A Comprehensive Foundation, Pearson Education, 2nd edition, 2003.
[10] S. Kumar, Neural Networks A Classroom Approach, Tata McGraw Hill, 8th Reprint, 2009.