Finger vein recognition using linear kernel entropy component analysis

Sepehr Damavandinejadmonfared

doi:10.1109/ICCP.2012.6356194

Finger vein recognition using linear kernel entropy component analysis

Sepehr Damavandinejadmonfared^*

^*Corresponding author for this work

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

13 Citations (Scopus)

Abstract

Based on the previous research, Kernel Entropy Component Analysis (KECA) is introduced as a more appropriate method than Kernel Principal Component Analysis (KPCA) for face recognition. In this paper, an algorithm using KECA is proposed to merit finger vein recognition. The proposed algorithm is then compared to Principal Component Analysis (PCA) and Different types of KECA in order to determine the most appropriate one in terms of finger vein recognition.

Original language	English
Title of host publication	Proceedings - 2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing, ICCP 2012
Pages	249-252
Number of pages	4
DOIs	https://doi.org/10.1109/ICCP.2012.6356194
Publication status	Published - 2012
Externally published	Yes
Event	2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing, ICCP 2012 - Cluj-Napoca Duration: 30 Aug 2012 → 1 Sept 2012

Other

Other	2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing, ICCP 2012
City	Cluj-Napoca
Period	30/08/12 → 1/09/12

Keywords

Biometrics
finger vein recognition
Kernel Entropy Component Analysis (KPCA)
Principal Component Analysis (PCA)

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10.1109/ICCP.2012.6356194

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@inproceedings{764c2a1dab5840b1bbb47cef718ec623,

title = "Finger vein recognition using linear kernel entropy component analysis",

abstract = "Based on the previous research, Kernel Entropy Component Analysis (KECA) is introduced as a more appropriate method than Kernel Principal Component Analysis (KPCA) for face recognition. In this paper, an algorithm using KECA is proposed to merit finger vein recognition. The proposed algorithm is then compared to Principal Component Analysis (PCA) and Different types of KECA in order to determine the most appropriate one in terms of finger vein recognition.",

keywords = "Biometrics, finger vein recognition, Kernel Entropy Component Analysis (KPCA), Principal Component Analysis (PCA)",

author = "Sepehr Damavandinejadmonfared",

year = "2012",

doi = "10.1109/ICCP.2012.6356194",

language = "English",

isbn = "9781467329514",

pages = "249--252",

booktitle = "Proceedings - 2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing, ICCP 2012",

note = "2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing, ICCP 2012 ; Conference date: 30-08-2012 Through 01-09-2012",

}

Damavandinejadmonfared, S 2012, Finger vein recognition using linear kernel entropy component analysis. in Proceedings - 2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing, ICCP 2012., 6356194, pp. 249-252, 2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing, ICCP 2012, Cluj-Napoca, 30/08/12. https://doi.org/10.1109/ICCP.2012.6356194

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T1 - Finger vein recognition using linear kernel entropy component analysis

AU - Damavandinejadmonfared, Sepehr

PY - 2012

Y1 - 2012

N2 - Based on the previous research, Kernel Entropy Component Analysis (KECA) is introduced as a more appropriate method than Kernel Principal Component Analysis (KPCA) for face recognition. In this paper, an algorithm using KECA is proposed to merit finger vein recognition. The proposed algorithm is then compared to Principal Component Analysis (PCA) and Different types of KECA in order to determine the most appropriate one in terms of finger vein recognition.

AB - Based on the previous research, Kernel Entropy Component Analysis (KECA) is introduced as a more appropriate method than Kernel Principal Component Analysis (KPCA) for face recognition. In this paper, an algorithm using KECA is proposed to merit finger vein recognition. The proposed algorithm is then compared to Principal Component Analysis (PCA) and Different types of KECA in order to determine the most appropriate one in terms of finger vein recognition.

KW - Biometrics

KW - finger vein recognition

KW - Kernel Entropy Component Analysis (KPCA)

KW - Principal Component Analysis (PCA)

UR - http://www.scopus.com/inward/record.url?scp=84871578133&partnerID=8YFLogxK

U2 - 10.1109/ICCP.2012.6356194

DO - 10.1109/ICCP.2012.6356194

M3 - Conference proceeding contribution

AN - SCOPUS:84871578133

SN - 9781467329514

SP - 249

EP - 252

BT - Proceedings - 2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing, ICCP 2012

T2 - 2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing, ICCP 2012

Y2 - 30 August 2012 through 1 September 2012

ER -

Finger vein recognition using linear kernel entropy component analysis

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