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Texture Feature Extraction using Partitioned/Sectorized Complex Planes in Transform Domain for Iris & Palmprint Recognition

Published on March 2012 by H B Kekre, V A Bharadi
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International Conference and Workshop on Emerging Trends in Technology
Foundation of Computer Science USA
ICWET2012 - Number 3
March 2012
Authors: H B Kekre, V A Bharadi
70ba8e0a-1096-4d9f-8061-283517437881

H B Kekre, V A Bharadi . Texture Feature Extraction using Partitioned/Sectorized Complex Planes in Transform Domain for Iris & Palmprint Recognition. International Conference and Workshop on Emerging Trends in Technology. ICWET2012, 3 (March 2012), 18-24.

@article{
author = { H B Kekre, V A Bharadi },
title = { Texture Feature Extraction using Partitioned/Sectorized Complex Planes in Transform Domain for Iris & Palmprint Recognition },
journal = { International Conference and Workshop on Emerging Trends in Technology },
issue_date = { March 2012 },
volume = { ICWET2012 },
number = { 3 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 18-24 },
numpages = 7,
url = { /proceedings/icwet2012/number3/5329-1020/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and Workshop on Emerging Trends in Technology
%A H B Kekre
%A V A Bharadi
%T Texture Feature Extraction using Partitioned/Sectorized Complex Planes in Transform Domain for Iris & Palmprint Recognition
%J International Conference and Workshop on Emerging Trends in Technology
%@ 0975-8887
%V ICWET2012
%N 3
%P 18-24
%D 2012
%I International Journal of Computer Applications
Abstract

Feature vector generation is an important step in biometric authentication. Biometric traits such as fingerprint, palmprint, iris, & finger-knuckle prints are rich in texture. This texture is unique and the feature vector extraction algorithm should correctly represent the texture pattern. In this paper a texture feature extraction methodology is proposed for iris and pamlprints. This method is based on one step transform of the two dimensional images and then using the intermediate transformation data to generate complex planes for feature vector generation. This method is implemented using Walsh, DCT, Hartley, Kekre Transform &Kekre Wavelets. Results indicate the effectiveness of the feature vector for biometric authentication.

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Index Terms

Computer Science
Information Sciences

Keywords

Biometrics Transforms DCT FFT Kekre Transform Hartley Transform Kekre Wavelets