Grip-Pattern Recognition in Smart Gun Based on Likelihood-Ratio Classifier and Support Vector Machine

X. Shang; Raymond N.J. Veldhuis

doi:10.1007/978-3-540-69905-7_33

Grip-Pattern Recognition in Smart Gun Based on Likelihood-Ratio Classifier and Support Vector Machine

X. Shang, Raymond N.J. Veldhuis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

4 Citations (Scopus)

1 Downloads (Pure)

Abstract

In the biometric verification system of a smart gun, the rightful user of a gun is recognized based on grip-pattern recognition. It was found that the verification performance of this system degrades strongly when the data for training and testing have been recorded in different sessions with a time lapse. This is due to the variations between the probe image and the gallery image of a subject. In this work the grip-pattern verification has been implemented based on both classifiers of the likelihood-ratio classifier and the support vector machine. It has been shown that the support vector machine gives much better results than the likelihood-ratio classifier if there are considerable variations between data for training and testing. However, once the variations are reduced by certain techniques and thus the data are better modelled during the training process, the support vector machine tends to lose its superiority.

Original language	English
Title of host publication	Image and Signal Processing
Subtitle of host publication	3rd International Conference, ICISP 2008. Cherbourg-Octeville, France, July 1-3, 2008. Proceedings
Place of Publication	Berlin
Publisher	Springer
Pages	289-295
Number of pages	7
ISBN (Print)	978-3-540-69904-0
DOIs	https://doi.org/10.1007/978-3-540-69905-7_33
Publication status	Published - 6 Jul 2008
Event	3rd International Conference on Image and Signal Processing, ICISP 2008 - Cherbourg-Octeville, France Duration: 1 Jul 2008 → 3 Jul 2008 Conference number: 3

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Verlag
Volume	5099
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Image and Signal Processing, ICISP 2008
Abbreviated title	ICISP
Country/Territory	France
City	Cherbourg-Octeville
Period	1/07/08 → 3/07/08

Keywords

EWI-14299
CR-I.5
IR-62576
METIS-254945
SCS-Safety

Access to Document

10.1007/978-3-540-69905-7_33

Cite this

Shang, X., & Veldhuis, R. N. J. (2008). Grip-Pattern Recognition in Smart Gun Based on Likelihood-Ratio Classifier and Support Vector Machine. In Image and Signal Processing: 3rd International Conference, ICISP 2008. Cherbourg-Octeville, France, July 1-3, 2008. Proceedings (pp. 289-295). (Lecture Notes in Computer Science; Vol. 5099). Springer. https://doi.org/10.1007/978-3-540-69905-7_33

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title = "Grip-Pattern Recognition in Smart Gun Based on Likelihood-Ratio Classifier and Support Vector Machine",

abstract = "In the biometric verification system of a smart gun, the rightful user of a gun is recognized based on grip-pattern recognition. It was found that the verification performance of this system degrades strongly when the data for training and testing have been recorded in different sessions with a time lapse. This is due to the variations between the probe image and the gallery image of a subject. In this work the grip-pattern verification has been implemented based on both classifiers of the likelihood-ratio classifier and the support vector machine. It has been shown that the support vector machine gives much better results than the likelihood-ratio classifier if there are considerable variations between data for training and testing. However, once the variations are reduced by certain techniques and thus the data are better modelled during the training process, the support vector machine tends to lose its superiority.",

keywords = "EWI-14299, CR-I.5, IR-62576, METIS-254945, SCS-Safety",

author = "X. Shang and Veldhuis, {Raymond N.J.}",

year = "2008",

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series = "Lecture Notes in Computer Science",

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Shang, X & Veldhuis, RNJ 2008, Grip-Pattern Recognition in Smart Gun Based on Likelihood-Ratio Classifier and Support Vector Machine. in Image and Signal Processing: 3rd International Conference, ICISP 2008. Cherbourg-Octeville, France, July 1-3, 2008. Proceedings. Lecture Notes in Computer Science, vol. 5099, Springer, Berlin, pp. 289-295, 3rd International Conference on Image and Signal Processing, ICISP 2008, Cherbourg-Octeville, France, 1/07/08. https://doi.org/10.1007/978-3-540-69905-7_33

Grip-Pattern Recognition in Smart Gun Based on Likelihood-Ratio Classifier and Support Vector Machine. / Shang, X.; Veldhuis, Raymond N.J.
Image and Signal Processing: 3rd International Conference, ICISP 2008. Cherbourg-Octeville, France, July 1-3, 2008. Proceedings. Berlin: Springer, 2008. p. 289-295 (Lecture Notes in Computer Science; Vol. 5099).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AB - In the biometric verification system of a smart gun, the rightful user of a gun is recognized based on grip-pattern recognition. It was found that the verification performance of this system degrades strongly when the data for training and testing have been recorded in different sessions with a time lapse. This is due to the variations between the probe image and the gallery image of a subject. In this work the grip-pattern verification has been implemented based on both classifiers of the likelihood-ratio classifier and the support vector machine. It has been shown that the support vector machine gives much better results than the likelihood-ratio classifier if there are considerable variations between data for training and testing. However, once the variations are reduced by certain techniques and thus the data are better modelled during the training process, the support vector machine tends to lose its superiority.

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Grip-Pattern Recognition in Smart Gun Based on Likelihood-Ratio Classifier and Support Vector Machine

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