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 personâs 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.
Highlights
A biometric system is basically a pattern recognition system which identifies a person by determining the authenticity of a specific physiological or behavioral features possessed by the user
The aim of this study is to propose an invariant moment’s algorithm based on wavelet transform to improve the accuracy rate and time performance and extract highly distinctive features from the palmprint without the effects of rotation, translation and scaling changes from one individual to another
The results show that the highest accuracy is obtained when both False Acceptance Rate (FAR) and False Rejection Rate (FRR) are equal to zero, this as in the set no. 1, 4 and 5
Summary
Technology have assisted human beings in performing Biometrics refers to the use of physiological or tasks which were previously difficult to carry out, or biological features to recognize the identity of an manually carried out A biometric system is basically a pattern recognition system which identifies a person by determining the authenticity of a specific physiological or behavioral features possessed by the user. May be defined as the automated methods of identifying or authenticating the identity of a living person based on physiological or behavioral traits. The system uses the physical properties of the individual in the biometric system, such as fingerprints, hand geometry, face, voice or iris They are more reliable and secure because they provide access to authorized users in the physical presence (Jain et al, 2006). The matching of patterns to be identified may be done by matching with only one template that is claimed person (Jain et al, 2004)
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