Finger vein recognition using linear Kernel Entropy Component Analysis

Author

Damavandinejadmonfared, Sepehr

Author_Institution

Sch. of Electr. & Electron. Eng., Univ. Sains Malaysia, Nibong Tebal, Malaysia

fYear

2012

fDate

Aug. 30 2012-Sept. 1 2012

Firstpage

249

Lastpage

252

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

entropy; principal component analysis; vein recognition; KECA; biometrics; finger vein recognition; linear kernel entropy component analysis; Accuracy; Entropy; Kernel; Principal component analysis; Thumb; Veins; Biometrics; Kernel Entropy Component Analysis (KPCA); Principal Component Analysis (PCA); finger vein recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computer Communication and Processing (ICCP), 2012 IEEE International Conference on

Conference_Location

Cluj-Napoca

Print_ISBN

978-1-4673-2953-8

Type

conf

DOI

10.1109/ICCP.2012.6356194

Filename

6356194

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2266362