Authorization based on palmprint

Xiao-Yong Wei; Dan Xu; Guo-Wu Yuan

doi:10.1007/11538059_19

Authorization based on palmprint

Xiao-Yong Wei
, Dan Xu
, Guo-Wu Yuan

Department of Computer Science

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

3 Citations (Scopus)

Abstract

In this paper, palmprint features were classified into Local Features and Global Features. Based on this definition, we discussed the advantage and weakness of each kind of features and presented a new palmprint identification algorithm using combination features. In this algorithm, a new method for capturing the key points of hand geometry was proposed. Then we described our new method of palmprint feature extracting. This method considered both the global feature and local detail of a palmprint texture and proposed a new kind of palmprint feature. The experimental results demonstrated the effectiveness and accuracy of these proposed methods. © Springer-Verlag Berlin Heidelberg 2005.

Original language	English
Pages (from-to)	174-183
Journal	Lecture Notes in Computer Science
Volume	3644
Issue number	PART I
DOIs	https://doi.org/10.1007/11538059_19
Publication status	Published - 2005
Event	1st International Conference on Intelligent Computing, ICIC 2005 - Hefei, China Duration: 23 Aug 2005 → 26 Aug 2005 https://link.springer.com/book/10.1007/11538356

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This work is supported by National Natural Science Foundation of China (NSFC.60162001).

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title = "Authorization based on palmprint",

abstract = "In this paper, palmprint features were classified into Local Features and Global Features. Based on this definition, we discussed the advantage and weakness of each kind of features and presented a new palmprint identification algorithm using combination features. In this algorithm, a new method for capturing the key points of hand geometry was proposed. Then we described our new method of palmprint feature extracting. This method considered both the global feature and local detail of a palmprint texture and proposed a new kind of palmprint feature. The experimental results demonstrated the effectiveness and accuracy of these proposed methods. {\textcopyright} Springer-Verlag Berlin Heidelberg 2005.",

author = "Xiao-Yong Wei and Dan Xu and Guo-Wu Yuan",

note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].; 1st International Conference on Intelligent Computing, ICIC 2005 ; Conference date: 23-08-2005 Through 26-08-2005",

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pages = "174--183",

journal = "Lecture Notes in Computer Science",

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TY - JOUR

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AU - Wei, Xiao-Yong

AU - Xu, Dan

AU - Yuan, Guo-Wu

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2005

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N2 - In this paper, palmprint features were classified into Local Features and Global Features. Based on this definition, we discussed the advantage and weakness of each kind of features and presented a new palmprint identification algorithm using combination features. In this algorithm, a new method for capturing the key points of hand geometry was proposed. Then we described our new method of palmprint feature extracting. This method considered both the global feature and local detail of a palmprint texture and proposed a new kind of palmprint feature. The experimental results demonstrated the effectiveness and accuracy of these proposed methods. © Springer-Verlag Berlin Heidelberg 2005.

AB - In this paper, palmprint features were classified into Local Features and Global Features. Based on this definition, we discussed the advantage and weakness of each kind of features and presented a new palmprint identification algorithm using combination features. In this algorithm, a new method for capturing the key points of hand geometry was proposed. Then we described our new method of palmprint feature extracting. This method considered both the global feature and local detail of a palmprint texture and proposed a new kind of palmprint feature. The experimental results demonstrated the effectiveness and accuracy of these proposed methods. © Springer-Verlag Berlin Heidelberg 2005.

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U2 - 10.1007/11538059_19

DO - 10.1007/11538059_19

M3 - RGC 21 - Publication in refereed journal

SN - 0302-9743

VL - 3644

SP - 174

EP - 183

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

IS - PART I

T2 - 1st International Conference on Intelligent Computing, ICIC 2005

Y2 - 23 August 2005 through 26 August 2005

ER -

Authorization based on palmprint

Abstract

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