research-article

Palmprint identification based on wide principal lines

Authors:

Hemantha Kumar Kalluri,

Munaga V. N. K. Prasad,

Arun AgarwalAuthors Info & Claims

ICACCI '12: Proceedings of the International Conference on Advances in Computing, Communications and Informatics

Pages 918 - 924

https://doi.org/10.1145/2345396.2345544

Published: 03 August 2012 Publication History

Abstract

In this paper, a novel palmprint identification and verification algorithm is proposed based on wide principal lines. A set of wide principal line extractors are devised. Later these wide principal line extractors are used to extract the wide principal lines. Morphological operators and grouping functions are used to eliminate the noise. In matching stage, a matching algorithm, based on pixel-to-pixel comparison is devised to calculate the similarity between the palmprints. In identification stage, wavelets and principal component analysis (PCA) are used for dimensionality reduction. Then Locally Discriminating Projection (LDP) is used to get the indexed list and the user is identified based on matching algorithm. The experimental results for the verification and identification on PolyU Database and Sub2D database are provided by Hong Kong Polytechnic University show that the discrimination of wide principal lines is also strong. With a minimum number of verifications, user is identified on these databases.

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Cited By

Jia Wzhou x(2024)Improved high-resolution network for palmprint principal line extractionThird International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024)10.1117/12.3032972(150)Online publication date: 5-Jul-2024
https://doi.org/10.1117/12.3032972
Ramakrishna Sajja VJhansi Lakshmi PBhupal Naik DKalluri H(2021)Student Performance Monitoring System Using Decision Tree ClassifierMachine Intelligence and Soft Computing10.1007/978-981-15-9516-5_33(393-407)Online publication date: 21-Jan-2021
https://doi.org/10.1007/978-981-15-9516-5_33

Index Terms

Palmprint identification based on wide principal lines
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Interest point and salient region detections

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Published In

cover image ACM Other conferences

ICACCI '12: Proceedings of the International Conference on Advances in Computing, Communications and Informatics

August 2012

1307 pages

ISBN:9781450311960

DOI:10.1145/2345396

Editors:
Sabu M. Thampi,
El-Sayed El-Afry,
Javier Aguiar,
General Chairs:
K. Gopalan
Purdue University Calumet
,
Sabu M. Thampi
Indian Institute of Information Technology and Management - Kerala, India

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 August 2012

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ICACCI '12: 2012 International Conference on Advances in Computing, Communications and Informatics

August 3 - 5, 2012

Chennai, India

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Cited By

Jia Wzhou x(2024)Improved high-resolution network for palmprint principal line extractionThird International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024)10.1117/12.3032972(150)Online publication date: 5-Jul-2024
https://doi.org/10.1117/12.3032972
Ramakrishna Sajja VJhansi Lakshmi PBhupal Naik DKalluri H(2021)Student Performance Monitoring System Using Decision Tree ClassifierMachine Intelligence and Soft Computing10.1007/978-981-15-9516-5_33(393-407)Online publication date: 21-Jan-2021
https://doi.org/10.1007/978-981-15-9516-5_33

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