Gender recognition from faces using bandlet and local binary patterns

Author

Alomar, Faten A. ; Muhammad, Ghulam ; Aboalsamh, Hatim ; Hussain, Mutawarra ; Mirza, Anwar M. ; Bebis, G.

Author_Institution

Coll. of Comput. & Inf. Sci., King Saud Univ., Riyadh, Saudi Arabia

fYear

2013

fDate

7-9 July 2013

Firstpage

59

Lastpage

62

Abstract

In this paper, multi-scale bandlet and local binary pattern (LBP) based method for gender recognition from faces is proposed. Bandlet is one of the multi-resolution techniques that can adapt the orientation of the edges of the face images, and thereby can better capture the texture of a face image. After extracting bandlet coefficients from face images at different scales, LBP is applied to create a histogram, which is used as the feature to a minimum distance classifier. The experiments are performed using FERET grayscale face database, and the highest accuracy of 99.13% is obtained with the proposed method.

Keywords

face recognition; gender issues; image resolution; image texture; FERET grayscale face database; face image texture; gender recognition; local binary pattern based method; minimum distance classifier; multiresolution techniques; multiscale bandlet; Accuracy; Databases; Face recognition; Histograms; Support vector machines; Transforms; FERET; Gender recognition; bandlet; face images;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Signals and Image Processing (IWSSIP), 2013 20th International Conference on

Conference_Location

Bucharest

ISSN

2157-8672

Print_ISBN

978-1-4799-0941-4

Type

conf

DOI

10.1109/IWSSIP.2013.6623449

Filename

6623449