首页    期刊浏览 2024年12月12日 星期四
登录注册

文章基本信息

  • 标题:PALMPRINT VERIFICATION USING INVARIANT MOMENTS BASED ON WAVELET TRANSFORM
  • 本地全文:下载
  • 作者:Hussein, Inass SH. ; Nordin, Md Jan
  • 期刊名称:Journal of Computer Science
  • 印刷版ISSN:1549-3636
  • 出版年度:2014
  • 卷号:10
  • 期号:8
  • 页码:1389-1396
  • DOI:10.3844/jcssp.2014.1389.1396
  • 出版社:Science Publications
  • 摘要: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.
  • 关键词:Biometric System; Verification; Invariant Moments; Roi; 2D Wavelet Ttransform
国家哲学社会科学文献中心版权所有