Spatial frequency domain image processing for biometric recognition

Author

Kumar, B. V K Vjaya ; Savvides, Marios ; Venkataramani, Krjthika ; Xie, Chunyan

Author_Institution

Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA

Volume

1

fYear

2002

fDate

2002

Abstract

Biometric recognition refers to the process of matching an input biometric to stored biometric information. In particular, biometric verification refers to matching the live biometric input from an individual to the stored biometric template about that individual. Examples of biometrics include face images, fingerprint images, iris images, retinal scans, etc. Thus, image processing techniques prove useful in the biometric recognition. We discuss spatial frequency domain image processing methods useful for biometric recognition.

Keywords

correlation methods; eye; face recognition; filtering theory; fingerprint identification; frequency-domain analysis; FFT; MACE filters; biometric recognition; biometric verification; closed-form expressions; correlation filters; distance classifier correlation filters; distortion-tolerance; face verification; fast fourier transforms; fingerprint images; image processing; iris images; live biometric input; minimum average correlation energy filters; optimal tradeoff filters; retinal scans; shift-invariance; spatial frequency domain image processing; stored biometric information; stored biometric template; Authentication; Biometrics; Biosensors; Face detection; Filters; Fingerprint recognition; Frequency domain analysis; Image processing; Image recognition; Iris;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing. 2002. Proceedings. 2002 International Conference on

ISSN

1522-4880

Print_ISBN

0-7803-7622-6

Type

conf

DOI

10.1109/ICIP.2002.1037957

Filename

1037957