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

被引：0

作者：

Kacar, Umit ^{[1
]}

Kirci, Murvet ^{[1
]}

Gunes, Ece Olcay ^{[1
]}

Inan, Tolga ^{[2
]}

机构：

[1] Istanbul Tech Univ, Elekt & Elekt Muhendisligi Bolumu, Istanbul, Turkey

[2] TED Univ, Elekt & Elekt Muhendisligi Bolumu, Ankara, Turkey

来源：

2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2015年

关键词：

Biometrics; 2D ear recognition; principal component analysis; linear discriminant analysis; Discriminative common vector approach; support vector machines;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：1260 / 1263

页数：4