Combination of off-line and on-line signature verification systems based on SVM and DST

AbstractThe widespread use of smartphones and the ability of these devices to digitize signatures have made it possible to sign electronic documents in this way. In this paper we compared two on-line signature databases in terms of verification performance: the MCYT containing signatures drawn by stylus pen, and MOBISIG containing finger drawn signatures. Performance evaluations were performed using both local and global systems. In the case of global systems, we evaluated the performance of a novel information theory features set. Little improvement was achieved by this feature set. There were large differences between the two databases in terms of performance. Finger drawn signatures collected by mobile device were proved inferior to signatures collected by digitizing tablet and its stylus.

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An Ensemble Based Offline Handwritten Signature Verification System

Statistics Optimization & Information Computing ◽

10.19139/soic-2310-5070-447 ◽

2020 ◽

Vol 8 (4) ◽

pp. 902-914

Author(s):

Alpana Deka ◽

Lipi B Mahanta

Keyword(s):

Naive Bayes ◽

Ensemble Methods ◽

Ensemble Classifier ◽

Naïve Bayes ◽

Signature Verification ◽

Support Vector ◽

Supervised Classifiers ◽

On Line ◽

Verification Systems ◽

Handwritten Signature

In the field of security and forgery prevention, handwritten signatures are the most widely recognized biometric since long and also most practical. Although handwritten signature verification systems are studied using both On-line and Off-line approaches, Off-line signature verification systems are more difficult to compare to On-line verification systems. This is due to the lack of dynamic information, viz. a database which constantly stores the latest signature of the person. In the paper an approach using ensemble methods are adopted to classify a signature as forgery or not. In proposed system, three classifiers, viz, one unsupervised, viz. Fuzzy C-Means (FCM) and two supervised classifiers, viz. Naive Bayes (NB) and Support Vector Machine (SVM) are used as base classifiers. An attempt is made to compare the different approaches. We attempt both the categories of classification not only because both of them are applicable in this particular case but also with an objective of finding out which performs better. In most cases it is observed that Naive Bayes and Ensemble are comparable as they exhibit better performance than the other two. But among them, in most of the cases Ensemble classifier performs better than the Naive Bayes and consequently we have taken the Ensemble as a final classifier.

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On-line Chinese signature verification based on the partition algorithm

International Workshop on Communication Technology 2013 ◽

10.2495/cecnet130751 ◽

2014 ◽

Author(s):

Yiming Qiu

Keyword(s):

Signature Verification ◽

On Line

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The Influence of Template Ageing on a Dynamic Signature Verification System

Journal of Forensic Document Examination ◽

10.31974/jfde24-47-52 ◽

2014 ◽

Vol 24 ◽

pp. 47-52

Author(s):

Joanna Putz-Leszczynska

Keyword(s):

Potential Risk ◽

Signature Verification ◽

Verification System ◽

Verification Systems ◽

Dynamic Signature

This paper addresses template ageing in automatic signature verification systems. Handwritten signatures are a behavioral biometric sensitive to the passage of time. The experiments in this paper utilized a database that contains signature realizations captured in three sessions. The last session was captured seven years after the first one. The results presented in this paper show a potential risk of using an automatic handwriting verification system without including template ageing Purchase Article for $10

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