Research Article
Review on Offline Signature Recognition and Verification Techniques
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 179 - Issue 53 |
| Published: Jun 2018 |
| Authors: Henali Patel, Shivani Desai, Pooja Desai, Abha Damani |
10.5120/ijca2018917233
|
Henali Patel, Shivani Desai, Pooja Desai, Abha Damani . Review on Offline Signature Recognition and Verification Techniques. International Journal of Computer Applications. 179, 53 (Jun 2018), 35-41. DOI=10.5120/ijca2018917233
@article{ 10.5120/ijca2018917233,
author = { Henali Patel,Shivani Desai,Pooja Desai,Abha Damani },
title = { Review on Offline Signature Recognition and Verification Techniques },
journal = { International Journal of Computer Applications },
year = { 2018 },
volume = { 179 },
number = { 53 },
pages = { 35-41 },
doi = { 10.5120/ijca2018917233 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2018
%A Henali Patel
%A Shivani Desai
%A Pooja Desai
%A Abha Damani
%T Review on Offline Signature Recognition and Verification Techniques%T
%J International Journal of Computer Applications
%V 179
%N 53
%P 35-41
%R 10.5120/ijca2018917233
%I Foundation of Computer Science (FCS), NY, USA
Abstract
A mark or sign made by an individual on an instrument or document to signify knowledge, approval, acceptance, or obligation. Signature recognition is a behavioural biometric that identifies an individual on the basis of their handwritten text. In this paper we have given description about signature recognition methods and have compared all those methods.
References
- D. Bertolini, L. S. Oliveira, E. Justino, and R. Sabourin. Reducing forgeries in writer-independent off-line signature verification through ensemble of classifiers. Pattern Recognition, 43(1), January 2010.
- R.K. Bharathi and B.H. Shekar. Off-line signature verification based on chain code histogram and Support Vector Machine. In 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pages 2063–2068, August 2013
- Alceu S. Britto, Robert Sabourin, and Luiz E. S. Oliveira. Dynamic selection of classifiers - a comprehensive review. Pattern Recognition, 47(11):3665–3680, November 2014.
- Rafael M. O. Cruz, Robert Sabourin, and George D. C. Cavalcanti. Dynamic classifier selection: Recent advances and perspectives. Information Fusion, 41:195–216, May 2018.
- G.S. Eskander, R. Sabourin, and E. Granger. Hybrid writer-independentwriter-dependent offline signature verification system. IET Biometrics, 2(4):169–181, December 2013.
- Shiwani Sthapak1, Minal Khopade2, Chetana Kashid3. Artificial Neural Network Based Signature Recognition & Verification.ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 3, Issue 8, and August 2013
- M.A. Ferrer, M. Diaz-Cabrera, and A. Morales. Synthetic off-line signature image generation. In 2013 International Conference on Biometrics (ICB), pages 1–7, June 2013.
- Ashwini Pansare, Shalini Bhatia “Off-line Signature Verification Using Neural Network”, International Journal of Scientific & Engineering Research, Volume 3, Issue 2, February-2012 1 ISSN 2229-5518
- S.T. Kolhe, S. E. Pawar, Dept. of Computer Engg, AVCOE, Sangamner, India, “Offline Signature Verification Using Neural Network”, International Journal of Modern Engineering Research (IJMER), Vol.2, Issue.3, May-June 2012 pp-1171-1175
- Luiz G. Hafemann, Robert Sabourin, and Luiz S. Oliveira. Analyzing features learned for offline signature verification using Deep CNNs. In International Conference on Pattern Recognition, pages 2989–2994, 2016.
- Cemil OZ, Sakarya University Computer Eng. Department, Sakarya, Turkey, Fikret Ercal, UMR Computer Science Department, Rolla, MO 65401, Zafer Demir, Sakaraya University electric electronic eng. Department sakarya, Turkey, “Signature Recognition and Verification with ANN”.
- Emre Özgündüz, Tülin Şentürk and M. Elif Karslıgil. OFF-LINE SIGNATURE VERIFICATION AND RECOGNITION BY SUPPORT VECTOR MACHINE.
- O.C Abikoye M.A Mabayoje R. Ajibade “Offline Signature Recognition & Verification using Neural Network”, Department of Computer Science University of Ilorin P.M.B 1515, Ilorin, Nigeria, International Journal of Computer Applications (0975 – 8887) Volume 35– No.2, December 2011
- Paigwar Shikha, Shukla Shailja, “Neural Network Based Offline Signature Recognition and Verification System”, Department of Electrical Engineering, Jabalpur Engineering College Jabalpur, MP, INDIA, Research Journal of Engineering Sciences ISSN 2278 – 9472, Vol. 2(2), 11-15, February (2013)
- Yu Qiao, Jianzhuang Liu, Department of Information Engineering the Chinese University of Hong Kong, Xiaoou Tang, Microsoft Research Asia Beijing, China, “Offline Signature Verification Using Online Handwriting Registration”.
- M. J. Alhaddad, D. Mohamad and A. M. Ahsan, “Online Signature Verification Using Probablistic Modeling and Neural Network”, IEEE, (2012)
- http://people revoledu.com/kardi/tutorial/KNN/Strength%20and%20weakness.htm
- https://www.quora.com/What-are-the-advantages-disadvantages-of-Artificial-Neural-networks
- https://docs.oracle.com/cd/B28359_01/datamine.111/b28129/algo_svm.htm#CHHDJFDJ
- http://www.svms.org/disadvantages.html
- https://www.pearl-scan.co.uk/blog/advantages-of-acr-optical-character-recognition
- http://www.meridianoutpost.com/resources/articals/ocr-limitations.php
- http://cmp.felk.cvut.cz/cmp/courses/dzo/resources/lecture_object-recognition.pdf.
- “A Review on the Various Techniques used for Optical Character Recognition”, Pranob K Charles, V. Harish, M. Swathi, CH. Deepthi/International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622, Vol. 2, Issue 1, Jan-Feb 2012.
Index Terms
Keywords