چکیده (انگلیسی):

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.