Classification of facial images

Author

Malkauthekar, Mahananda D.

Author_Institution

Govt. Eng. Coll., Karad, India

fYear

2011

fDate

23-24 March 2011

Firstpage

507

Lastpage

511

Abstract

This paper consists of development of detection strategies for face recognition tasks and to access its feasibility for forensic analysis using the FERET face database Author has used global feature extraction technique using statistical method for image classification. Facial images of three subjects with different expression and angles are used for classification. Principal Component Analysis has been used for three classes. Mahalanobis distance and Euclidian distance are used as similarity measures and a result of both methods is compared.

Keywords

computer forensics; face recognition; image classification; principal component analysis; Euclidian distance; FERET face database; Mahalanobis distance; face recognition; facial image classification; forensic analysis; global feature extraction technique; principal component analysis; similarity measures; statistical method; Databases; Euclidean distance; Face; Face recognition; Image recognition; Principal component analysis; Training; Euclidian distance; FERET database; Image Classification; Mahalanobis distance; PCA; Principal Component Analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Trends in Electrical and Computer Technology (ICETECT), 2011 International Conference on

Conference_Location

Tamil Nadu

Print_ISBN

978-1-4244-7923-8

Type

conf

DOI

10.1109/ICETECT.2011.5760168

Filename

5760168