Palmprint verification using invariant moments based on wavelet transform

Inass S H Hussein, Md. Jan Nordin

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Data security is one of the important issues among computer users. Data security can prevent fraudulent users from accessing an individual's personal data. The biometrics recognition as one of the most important parts in the security of the data and the application of computer vision. The biometrics is the authentication method used in a wide variety of applications such as e-banking, e-commerce, e-government and many others. A biometric system is one which requires the recognition of a pattern, whereby it enables the differentiation of features from one individual to another. Biometric technologies, thus may be defined as the automated methods of identifying, or authenticating, the identity of a living person based on physiological or behavioral traits. This study emphasizes palmprint recognition, which provides a wide deployment range of authentication methods. The palmprint contains principal lines, wrinkles, fine lines, ridges and surface area; thus the palmprint of person differs from one to another. Previous researchers have difficulty extracting the features of a palm print, because of the effects of rotation, translation and scaling changes and the accuracy rate of verification performance needs to be improved. The aim of this study is to extract shape features using an invariant moments algorithm based on wavelet transform and identify the person's verification. This model has shown a promising results without the effects of rotation, translation and scaling of objects, because it is associated with the use of a good description of shape features. This system has been tested using databases from the Indian Institute of Technology, Kanpur (IITK), by using the False Rejection Rate (FRR) and False Acceptance Rate (FAR), we may calculate the accuracy rate of verification. The experiment shows a 97.99% accuracy rate of verification.

Original languageEnglish
Pages (from-to)1389-1396
Number of pages8
JournalJournal of Computer Science
Volume10
Issue number8
DOIs
Publication statusPublished - 2014

Fingerprint

Biometrics
Wavelet transforms
Security of data
Authentication
Palmprint recognition
Data privacy
Computer vision
Experiments

Keywords

  • 2D wavelet ttransform
  • Biometric system
  • Invariant moments
  • Roi
  • Verification

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

Palmprint verification using invariant moments based on wavelet transform. / Hussein, Inass S H; Nordin, Md. Jan.

In: Journal of Computer Science, Vol. 10, No. 8, 2014, p. 1389-1396.

Research output: Contribution to journalArticle

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