An Efficient Automated Attendance Entering System by Eliminating Counterfeit Signatures using Kolmogorov Smirnov Test

Lokesha Weerasinghe; B.H. Sudantha

An Efficient Automated Attendance Entering System by Eliminating Counterfeit Signatures using Kolmogorov Smirnov Test

Lokesha Weerasinghe * §

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B.H. Sudantha

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§ Sri Lanka Institute of Information Technology, Malabe

An Efficient Automated Attendance Entering System by Eliminating Counterfeit Signatures using Kolmogorov Smirnov Test

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Abstract

Maintaining the attendance database of thousands of students has become a tedious task in the universities in Sri Lanka. This paper comprises of 3 phases: signature extraction, signature recognition, and signature verification to automate the process. We applied necessary image processing techniques, and extracted useful features from each signature. Support Vector Machine (SVM), multiclass Support Vector Machine and Kolmogorov Smirnov test is used to signature classification, recognition, and verification respectively. The described method in this report represents an effective and accurate approach to automatic signature recognition and verification. It is capable of matching, classifying, and verifying the test signatures with the database of 83.33%, 100%, and 100% accuracy respectively.

References

20 Cites in Article

Reference Format

R Banka,F Nourbakhsh (2010). Extraction of Signature and Handwritten Regions from Official Binary document Images.
D Bhattacharyya,T Kim (2010). Design of artificial neural network for handwritten signature recognition.
J Coetzer (2005). Off-line signature verification.
İ Cüceloğlu,H Oğul (2014). Detecting handwritten signatures in scanned documents.
R Gonzalez,R Woods (2002). Digital image processing.
C Gupta,U Dixit (2015). A Review on Signature Detection and Signature Based Document Image Retrieval.
Luiz Hafemann,Robert Sabourin,Luiz Oliveira (2015). Offline handwritten signature verification — Literature review.
Meenakshi Kalera,Sargur Srihari,Aihua Xu (2004). OFFLINE SIGNATURE VERIFICATION AND IDENTIFICATION USING DISTANCE STATISTICS.
Ali Karouni,Bassam Daya,Samia Bahlak (2010). Offline signature recognition using neural networks approach.
G Khuwaja,M Laghari (2011). Offline handwritten signature recognition.
V Kiani,R Pourreza,H Pourreza (2009). Offline signature verification using local radon transform and support vector machines.
P Kumar,S Singh,A Garg,N Prabhat (2013). Hand written signature recognition & verification using neural network.
R Mehra,R Gangwar (2014). A Survey: Enhanced Offline Signature Recognition Using Neuro-Fuzzy and SURF Features Techniques.
V Nguyen,M Blumenstein,V Muthukkumarasamy,G Leedham (2007). Off-line signature verification using enhanced modified direction features in conjunction with neural classifiers and support vector machines.
Emre Özgündüz,Tülin Şentürk,M Karslıgil (2005). Efficient Off-Line Verification and Identification of Signatures by Multiclass Support Vector Machines.
A Piyush Shanker,A Rajagopalan (2007). Off-line signature verification using DTW.
N Pushpalatha,A Gautam (2014). Offline signature Verification using spatial domain feature sets and support vector machine.
M Shirdhonkar,M Kokare (2010). Discrimination between printed and handwritten text in documents.
N Singh,S Kaushal (2015). Off-Line Signature Recognition Using Modified Neural Networks Approach.
K Sisodia,S Anand (2009). Off-line handwritten signature verification using artificial neural network classifier.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Lokesha Weerasinghe, B.H. Sudantha. 2019. "An Efficient Automated Attendance Entering System by Eliminating Counterfeit Signatures using Kolmogorov Smirnov Test". Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 19 (GJCST Volume 19 Issue G2).

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GJCST Volume 19 Issue G2

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

GJCST-G Classification K.3.0

Submission ReceivedDecember 7, 2018
Peer Review Double Blind
Handling Editor
Accepted December 31, 2018
Published January 15, 2019

Version of record

v1.2

Issue date

May 27, 2019

Language

English

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Article Matrices

Total Score: 142

Country: Sri Lanka

Subject: Global Journal of Computer Science and Technology

Authors: Lokesha Weerasinghe, B.H. Sudantha (PhD/Dr. count: 0)

View Count (all-time): 442

Total Views (Real + Logic): 1624

Total Downloads (simulated): 100

Publish Date: 2019 01, Tue

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