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Feature Vector Extraction based Texture Feature using Hybrid Wavelet Type I and II for Finger Knuckle Prints

Published on September 2015 by Vandana Yadav, Vinayak A Bharadi
journal_cover_thumbnail

International Conference and Workshop on Communication, Computing and Virtualization
Foundation of Computer Science USA
ICWCCV2015 - Number 1
September 2015
Authors: Vandana Yadav, Vinayak A Bharadi
e7343725-d84d-463e-8560-328c34e431b8

Vandana Yadav, Vinayak A Bharadi . Feature Vector Extraction based Texture Feature using Hybrid Wavelet Type I and II for Finger Knuckle Prints. International Conference and Workshop on Communication, Computing and Virtualization. ICWCCV2015, 1 (September 2015), 0-0.

@article{
author = { Vandana Yadav, Vinayak A Bharadi },
title = { Feature Vector Extraction based Texture Feature using Hybrid Wavelet Type I and II for Finger Knuckle Prints },
journal = { International Conference and Workshop on Communication, Computing and Virtualization },
issue_date = { September 2015 },
volume = { ICWCCV2015 },
number = { 1 },
month = { September },
year = { 2015 },
issn = 2249-0868,
pages = { 0-0 },
numpages = 1,
url = { /proceedings/icwccv2015/number1/789-1558/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and Workshop on Communication, Computing and Virtualization
%A Vandana Yadav
%A Vinayak A Bharadi
%T Feature Vector Extraction based Texture Feature using Hybrid Wavelet Type I and II for Finger Knuckle Prints
%J International Conference and Workshop on Communication, Computing and Virtualization
%@ 2249-0868
%V ICWCCV2015
%N 1
%P 0-0
%D 2015
%I International Journal of Applied Information Systems
Abstract

The finger knuckle print (FKP) of a particular person is found to be unique and can serve as a biometric feature has been revealed recently by the researchers. In this paper finger knuckle print will be used as a biometric feature. The databaseImages from Hong KongPolytechnic Universitywere processed using Kekre's hybrid wavelet type 1 and type 2 for the generation of results. Kekre's hybrid wavelet type 1 and type 2 were used for feature extraction from the images in order to process it further. The important role of hybrid wavelet transform is to combine the key features of two different orthogonal transforms so that the strengths of both the transform wavelets are used. The hybrid wavelet transforms can be generated using orthogonal transforms such as Discrete Cosine transform (DCT), Walsh transform, Discrete Kekre transform etc. In this paper the different transforms like (Discrete Cosine Transform) DCT, Haar. Hartley, Walsh and Kekre are used in any combination for generation of hybrid wavelets. These hybrid wavelets are applied on the database images to generate feature vector coefficients plotted in graph format and their distances are compared. The intra class and inter class distances are compared in this paper.

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Index Terms

Computer Science
Information Sciences

Keywords

Finger knuckle print (FKP) hybrid wavelet region of interest (ROI) Transform.