A comparison of PCA, LDA and DCVA in ear biometrics classification using SVM

Author

Kacar, Umit ; Kirci, Murvet ; Gunes, Ece Olcay ; Inan, Tolga

Author_Institution

Elektrik ve Elektron. Muhendisligi Bolumu, Istanbul Tek. Univ., İstanbul, Turkey

fYear

2015

fDate

16-19 May 2015

Firstpage

1260

Lastpage

1263

Abstract

Despite increasing three dimensional recognition rate in ear biometric, there is need for special equipment to three dimensional image. Ear biometrics recognition rate was obtained high success by combined distinctive common vector approach methods with support vector machines in two-dimensional low-resolution cameras used surveillance and security system. In particular, this method will provide an important contribution to the non-cooperative personnel identification.

Keywords

biometrics (access control); ear; image classification; image resolution; principal component analysis; security; support vector machines; surveillance; DCVA; LDA; PCA; SVM; ear biometrics classification; ear biometrics recognition; low-resolution cameras; security system; support vector machines; surveillance; three dimensional recognition rate; Art; Biometrics (access control); Ear; Pattern analysis; Support vector machines; Three-dimensional displays; Uniform resource locators; 2D ear recognition; Biometrics; Discriminative common vector approach; linear discriminant analysis; principal component analysis; support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications Conference (SIU), 2015 23th

Conference_Location

Malatya

Type

conf

DOI

10.1109/SIU.2015.7130067

Filename

7130067