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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/5624
Title: Analysis of 3D signatures recorded using leap motion sensor
Authors: Behera S.K.
Dogra D.P.
Pratim Roy, Partha
Published in: Multimedia Tools and Applications
Abstract: Signature recognition is identifying the signature’s owner, whereas verification is the process to find whether a signature is genuine or forged. Though, both are important in the field of forensic sciences, however, verification is more important to banks and credit card companies. In this paper, we have proposed a methodology to analyze 3D signatures captured using Leap motion sensor. We have extended existing 2D features into 3D from raw signatures and applied well-known classifiers for recognition as well as verification. We have shown that the 3rd dimension, which essentially represents instantaneous pressure during writing, can improve the accuracy of the biometric systems. We have created a large dataset containing more than 2000 signatures registered by 100 volunteers using the Leap motion interface. This has been made available online for the research community. Our analysis shows that, the proposed 3D extension is better than its original 2D version. Recognition and verification accuracy have increased by 6.8% and 9.5%, respectively using k-NN. Similarly, accuracy has increased by 9.9% (recognition) and 6.5% (verification) when HMM is used as the classifier. Similar results have been recorded on benchmark datasets. A comparison with 2D tablet-stylus interface has been carried out which also supports our claims. We believe, Leap motion can be an alternative to the existing biometric setups. © 2017, Springer Science+Business Media, LLC.
Citation: Multimedia Tools and Applications (2018), 77(11): 14029-14054
URI: https://doi.org/10.1007/s11042-017-5011-4
http://repository.iitr.ac.in/handle/123456789/5624
Issue Date: 2018
Publisher: Springer New York LLC
Keywords: 3D sequence analysis
Signature recognition
Signature verification
ISSN: 13807501
Author Scopus IDs: 37057132600
35408975400
56880478500
Author Affiliations: Behera, S.K., School of Electrical Sciences, IIT Bhubaneswar, Bhubaneswar, India
Dogra, D.P., School of Electrical Sciences, IIT Bhubaneswar, Bhubaneswar, India
Roy, P.P., Department of Computer Science and Engineering, IIT Roorkee, Roorkee, India
Corresponding Author: Behera, S.K.; School of Electrical Sciences, IIT BhubaneswarIndia; email: sb29@iitbbs.ac.in
Appears in Collections:Journal Publications [CS]

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