Optical wavelet subband filtering for joint transform correlation

Chau-Jern Cheng, Li Chien Lin

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

This work presents an experimental demonstration of an optical joint transform correlator based on the wavelet subband filter for texture pattern recognition. The optical wavelet subband filter is implemented using 4f filtering architecture and utilized to extract the texture features of fingerprints under noisy environments through frequency-and orientation-selective properties. The filtered texture features with noise reduction are applied to optimize recognition via joint transform correlation. Experimental results show that the optical wavelet subband filter enhances the significant texture features from corrupted fingerprints and increases the pattern discrimination of the joint transform correlator.

Original languageEnglish
Article number105001
JournalOptical Engineering
Volume44
Issue number10
DOIs
Publication statusPublished - 2005 Oct 1

Fingerprint

textures
Textures
Correlators
correlators
filters
Noise abatement
noise reduction
pattern recognition
Pattern recognition
discrimination
Demonstrations

Keywords

  • Joint transform correlator
  • Optical pattern recognition
  • Wavelet transform

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering(all)

Cite this

Optical wavelet subband filtering for joint transform correlation. / Cheng, Chau-Jern; Lin, Li Chien.

In: Optical Engineering, Vol. 44, No. 10, 105001, 01.10.2005.

Research output: Contribution to journalArticle

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