In this Paper, the actual presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. In this paper, we present a novel software-based fake detection method that can be used in multiple biometric systems to detect differ...

To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. In this paper, we present a novel softwarebased fake detection method that can be used in multiple biometric systems to detect different ty...

Abstract Biometric is an emerging technique for user authentication thanks to its efficiency compared the traditional methods, such as passwords and access-cards. However, most existing biometric systems require cooperation of users provide only a login time authentication. To address these drawbacks, we propose in this paper new, efficient continuous scheme based on newly trait that still unde...

Hand dorsal biometric recognition system proposed in this study combines the strength of information regions vein trait a deep learning based Convolutional Neural Networks (CNN) model. The approach divides each image into five overlapping regions; consequently, different training and test sets are obtained for image, modeling multi-modal while using only one trait. outputs combined by score-lev...

Many biometric systems, such as face, fingerprint and iris have been studied extensively for personal verification and identification purposes. Biometric identification with vein patterns is a more recent approach that uses the vast network of blood vessels underneath a person’s skin. These patterns in the hands are assumed to be unique to each individual and they do not change over time except...

The biometric-based systems (BMS) have proved enormously superior and accurate authentication mechanism as compared to conventional methods. The accuracy of recognition systems is further enhanced by using multi-modal biometric systems (MBS) with additional cost overhead. The BS based human recognition works by extracting unique feature points from the raw biological trait of the user, captured...

Biometrics refers to a scientific discipline which involves automatic methods for recognizing people based on their physiological or behavioural characteristics. Biometric systems that use a single trait are called unimodal systems, whereas those that integrate two or more traits are referred to as multimodal biometric systems. A multimodal biometric system requires an integration scheme to fus...

To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. In this paper, we present a novel software-based fake detection method that can be used in multiple biometric systems to detect different t...

In this paper, we introduced a new video-based spatio-temporal identification system and we also presented our initial identity authentication results based on the spontaneous pupillary oscillation features. We demonstrated that this biometric trait has the capability to provide enough discriminative information to authenticate the identity of a subject. We described the methodology to compute ...

Iris is a physiological biometric trait, which is unique among all biometric traits to recognize person effectively. In this paper we propose Multi-scale Independent Component Analysis (ICA) based Iris Recognition using Binarized Statistical Image Features (BSIF) and Histogram of Gradient orientation (HOG). The Left and Right portion is extracted from eye images of CASIA V 1.0 database leaving ...