Face recognition using Kernel Fisher´s Discriminant Analysis and nearest neighbor

Author

Setyawan, Iwan ; Putra, Abraham F. ; Timotius, Ivanna K. ; Febrianto, Andreas A.

Author_Institution

Dept. of Electron. Eng., Satya Wacana Christian Univ., Salatiga, Indonesia

fYear

2011

fDate

20-21 Oct. 2011

Firstpage

5

Lastpage

7

Abstract

Face recognition is a technology that is achieving more and more prominence today. This technology is now found in various applications such as automatic photo tagging and identification of criminal suspects. While the task of recognizing faces is easy for humans, the task of teaching a computer to do so is very challenging. This paper presents a face recognition system based on the Kernel Fishers Discriminant Analysis (KFDA) and Nearest Neighbor (NN) algorithms. We use the KFDA algorithm as a feature extractor and the NN algorithm as a classifier. Our current implementation of the system has achieved a recognition success rate of more than 83%.

Keywords

face recognition; feature extraction; pattern classification; statistical analysis; KFDA; NN algorithm; face recognition; feature extractor; kernel Fisher discriminant analysis; nearest neighbor algorithm; Algorithm design and analysis; Classification algorithms; Face; Face recognition; Feature extraction; Kernel; Vectors; Face recognition; Kernel Fisher´s Discriminant Analysis; Nearest Neighbor;

fLanguage

English

Publisher

ieee

Conference_Titel

Telecommunication Systems, Services, and Applications (TSSA), 2011 6th International Conference on

Conference_Location

Bali

Print_ISBN

978-1-4577-1441-2

Type

conf

DOI

10.1109/TSSA.2011.6095396

Filename

6095396