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

Kacar U., Kırcı M., Güneş E. O., Inan T.

23nd Signal Processing and Communications Applications Conference (SIU), Malatya, Turkey, 16 - 19 May 2015, pp.1260-1263 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu.2015.7130067
  • City: Malatya
  • Country: Turkey
  • Page Numbers: pp.1260-1263
  • Keywords: Biometrics, 2D ear recognition, principal component analysis, linear discriminant analysis, Discriminative common vector approach, support vector machines
  • TED University Affiliated: Yes

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 noncooperative personnel identification.