Face recognition improvement using soft biometrics

Author

El Kissi Ghalleb, Asma ; Sghaier, Souhir ; Ben Amara, Najoua Essoukri

Author_Institution

Nat. Eng. Sch. of Monastir, Univ. of Sousse, Sousse, Tunisia

fYear

2013

fDate

18-21 March 2013

Firstpage

1

Lastpage

6

Abstract

In this work we are interested in soft facial biometrics, a new field that aims at strengthening the performance of primary biometric systems based on traditional ways of biological type (DNA, saliva), morphological (face, iris, fingerprint) or behavioral (signature, handwriting, voice). We propose three types of facial soft biometrics: facial measurements, skin color and hair color. The results show that the fusion of these modalities with the primary face recognition system based on wavelet characterization and SVM training has increased the recognition rate and has decreased the equal error rate.

Keywords

DNA; biometrics (access control); face recognition; feature extraction; image colour analysis; image fusion; skin; support vector machines; wavelet transforms; DNA; SVM training; behavioral characteristics; biological characteristics; equal error rate; face; face recognition improvement; facial measurements; fingerprint; hair color; handwriting; iris; modality fusion; morphological characteristics; primary biometric system performance improvement; primary face recognition system; recognition rate; saliva; signature; skin color; soft facial biometrics; voice; wavelet characterization; Biometrics (access control); Color; Face; Hair; Image color analysis; Mouth; Skin; Biometrics; fusion of the primary system with the soft one; primary biometric system; soft biometric system;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Signals & Devices (SSD), 2013 10th International Multi-Conference on

Conference_Location

Hammamet

Print_ISBN

978-1-4673-6459-1

Electronic_ISBN

978-1-4673-6458-4

Type

conf

DOI

10.1109/SSD.2013.6564044

Filename

6564044