DocumentCode :
714500
Title :
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
Link To Document :
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