Enhancing Security of Biometric Systems Using Deep Features of Hand Biometrics

2019 ◽  
Author(s):  
Salim Chitroub ◽  
Abdallah Meraoumia ◽  
L. Laimeche ◽  
H. Bendjenna
Keyword(s):  
Biometric Systems ◽  
Hand Biometrics

A Review on Contactless Hand Verification Systems

2021 ◽  
pp. 126-136
Author(s):  
Santa Maria Shithil ◽  
Mashiwat Tabassum Waishy ◽  
Lomat Haider Chowdhury
Keyword(s):  
Convenient Method ◽  
State Of The Art ◽  
The State ◽  
Biometric System ◽  
Individual Person ◽  
Biometric Systems ◽  
Hand Biometrics ◽  
Verification Systems ◽  
Biometric Information ◽  
Sophisticated Technology

Biometric system is gaining popularity increasingly since it provides the most sophisticated technology for authentication, verification, and identification. This technology can identify each individual person on the basis of their biometric information such as their face, hand features, signatures, DNA, or iris pattern and thus can impart a secure and convenient method for authentication purposes. Hand biometrics is one of the most widely used biometric systems. There are two approaches for capturing hand biometrics: contact-based and contactless. In this paper, we present a thorough review of the state of the art contactless hand verification systems. We also present the various modules of the general contactless hand verification system and analyze various hand biometrics features.

Human Ear Pattern Recognition System

2017 ◽  
Vol 7 (8) ◽  
pp. 117 ◽  
Author(s):  
V. Jagan Naveen ◽  
K. Krishna Kishore ◽  
P. Rajesh Kumar
Keyword(s):  
Pattern Recognition ◽  
Expectation Maximization Algorithm ◽  
Recognition System ◽  
Modern World ◽  
Person Identification ◽  
Biometric Systems ◽  
Different Types ◽  
Recognition Systems ◽  
Human Ear ◽  
Pca Algorithm

In the modern world, human recognition systems play an important role to   improve security by reducing chances of evasion. Human ear is used for person identification .In the Empirical study on research on human ear, 10000 images are taken to find the uniqueness of the ear. Ear based system is one of the few biometric systems which can provides stable characteristics over the age. In this paper, ear images are taken from mathematical analysis of images (AMI) ear data base and the analysis is done on ear pattern recognition based on the Expectation maximization algorithm and k means algorithm.  Pattern of ears affected with different types of noises are recognized based on Principle component analysis (PCA) algorithm.

Iris segmentation for non-ideal Iris biometric systems

2021 ◽  
Author(s):  
Farmanullah Jan ◽  
Saleh Alrashed ◽  
Nasro Min-Allah
Keyword(s):  
Iris Segmentation ◽  
Biometric Systems

Multimodal biometric system using deep learning based on face and finger vein fusion

2021 ◽  
pp. 1-13
Author(s):  
Shikhar Tyagi ◽  
Bhavya Chawla ◽  
Rupav Jain ◽  
Smriti Srivastava
Keyword(s):  
High Performance ◽  
Recognition Accuracy ◽  
Error Rates ◽  
Facial Features ◽  
Biometric System ◽  
Deep Convolutional Neural Networks ◽  
Finger Vein ◽  
Biometric Systems ◽  
Overall Performance ◽  
Recognition Systems

Single biometric modalities like facial features and vein patterns despite being reliable characteristics show limitations that restrict them from offering high performance and robustness. Multimodal biometric systems have gained interest due to their ability to overcome the inherent limitations of the underlying single biometric modalities and generally have been shown to improve the overall performance for identification and recognition purposes. This paper proposes highly accurate and robust multimodal biometric identification as well as recognition systems based on fusion of face and finger vein modalities. The feature extraction for both face and finger vein is carried out by exploiting deep convolutional neural networks. The fusion process involves combining the extracted relevant features from the two modalities at score level. The experimental results over all considered public databases show a significant improvement in terms of identification and recognition accuracy as well as equal error rates.

scholarly journals Directed Gaze Trajectories for Biometric Presentation Attack Detection

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1394
Author(s):  
Asad Ali ◽  
Sanaul Hoque ◽  
Farzin Deravi
Keyword(s):  
Eye Movements ◽  
Visual Stimuli ◽  
Attack Detection ◽  
Movement Data ◽  
Biometric Systems ◽  
Planar Geometries ◽  
Presentation Attack Detection

Presentation attack artefacts can be used to subvert the operation of biometric systems by being presented to the sensors of such systems. In this work, we propose the use of visual stimuli with randomised trajectories to stimulate eye movements for the detection of such spoofing attacks. The presentation of a moving visual challenge is used to ensure that some pupillary motion is stimulated and then captured with a camera. Various types of challenge trajectories are explored on different planar geometries representing prospective devices where the challenge could be presented to users. To evaluate the system, photo, 2D mask and 3D mask attack artefacts were used and pupillary movement data were captured from 80 volunteers performing genuine and spoofing attempts. The results support the potential of the proposed features for the detection of biometric presentation attacks.

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