Treffer: Pattern discrimination of joint transform correlator based on wavelet subband filtering

Title:
Pattern discrimination of joint transform correlator based on wavelet subband filtering
Source:
Optics communications. 233(4-6):283-296
Publisher Information:
Amsterdam: Elsevier Science, 2004.
Publication Year:
2004
Physical Description:
print, 24 ref
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Communications Engineering, Feng Chia University, Taichung, Tawain, Province of China
Department of Electro-Optical Engineering, National Taipei University of Technology, Taipei 10608, Tawain, Province of China
ISSN:
0030-4018
Rights:
Copyright 2004 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Physics: optics
Accession Number:
edscal.15541193
Database:
PASCAL Archive

Weitere Informationen

We propose and demonstrate a Gabor wavelet prefiltering prior to classical and binarized joint transform correlator implementation to enhance texture features of fingerprints. The frequency- and orientation-selective properties of the wavelet subband filter are utilized to extract important textural features for optimal correlation recognition. A selection criterion for wavelet subbands is derived, and it is shown that the maximum signal-to-noise ratio of the correlator is achieved by optimizing the threshold level. Simulation results show that the proposed method increases the discrimination power of the correlator, especially under noisy environments.