Heterogeneous face biometrics based on Guassian weights and invariant features synthesis

2011 ◽  
Author(s):  
Mengyi Liu ◽  
Wei Xie ◽  
Xingwei Chen ◽  
Yufeng Ma ◽  
Yujing Guo ◽  
...  
Keyword(s):  
Invariant Features ◽  
Face Biometrics

Image quality assessment based on local invariant features

2013 ◽  
Vol 32 (12) ◽  
pp. 3369-3372 ◽  
Author(s):  
Ya-zhou YANG ◽  
Xiao-qing YING ◽  
Guang-quan CHENG ◽  
Dan TU
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Local Invariant ◽  
Invariant Features ◽  
Local Invariant Features

Secure Watermarking using Diophantine Equations for Authentication and Recovery

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Jayashree Nair ◽  
T. Padma
Keyword(s):  
Diophantine Equation ◽  
Diophantine Equations ◽  
Jpeg Compression ◽  
Authentication Scheme ◽  
Original Image ◽  
Invariant Features ◽  
Jpeg2000 Compression ◽  
Frequency Properties ◽  
Visual Authentication

This paper describes an authentication scheme that uses Diophantine equations based generation of the secret locations to embed the authentication and recovery watermark in the DWT sub-bands. The security lies in the difficulty of finding a solution to the Diophantine equation. The scheme uses the content invariant features of the image as a self-authenticating watermark and a quantized down sampled approximation of the original image as a recovery watermark for visual authentication, both embedded securely using secret locations generated from solution of the Diophantine equations formed from the PQ sequences. The scheme is mildly robust to Jpeg compression and highly robust to Jpeg2000 compression. The scheme also ensures highly imperceptible watermarked images as the spatio –frequency properties of DWT are utilized to embed the dual watermarks.

scholarly journals Privacy–Enhancing Face Biometrics: A Comprehensive Survey

2021 ◽  
pp. 1-1
Author(s):  
Blaz Meden ◽  
Peter Rot ◽  
Philipp Terhorst ◽  
Naser Damer ◽  
Arjan Kuijper ◽  
...  
Keyword(s):  
Comprehensive Survey ◽  
Face Biometrics

Algorithmic Analysis of Automatic Attendance System using Facial Recognition

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Face Recognition ◽  
Daily Life ◽  
Real Life ◽  
Student Attendance ◽  
Surveillance Camera ◽  
Daily Life Activities ◽  
The Face ◽  
Algorithmic Analysis ◽  
Human Faces ◽  
Face Biometrics

Attendance management can become a tedious task for teachers if it is performed manually.. This problem can be solved with the help of an automatic attendance management system. But validation is one of the main issues in the system. Generally, biometrics are used in the smart automatic attendance system. Managing attendance with the help of face recognition is one of the biometric methods with better efficiency as compared to others. Smart Attendance with the help of instant face recognition is a real-life solution that helps in handling daily life activities and maintaining a student attendance system. Face recognition-based attendance system uses face biometrics which is based on high resolution monitor video and other technologies to recognize the face of the student. In project, the system will be able to find and recognize human faces fast and accurately with the help of images or videos that will be captured through a surveillance camera. It will convert the frames of the video into images so that our system can easily search that image in the attendance database.

Intelligent Secure Smart Locking System using Face Biometrics

2021 ◽  
Author(s):  
Nagasree Y Lakshmi Venkata ◽  
Ch. Rupa ◽  
B Dharmika ◽  
Teja G Nithin ◽  
N Vineela
Keyword(s):  
Face Biometrics

MATCH SCORE FUSION OF FINGERPRINT AND FACE BIOMETRICS FOR VERIFICATION

2015 ◽  
Vol 77 (18) ◽  
Author(s):  
Chiung Ching Ho ◽  
Mufaddal Ali Hussin ◽  
Hu Ng
Keyword(s):  
Feature Vector ◽  
Product Rule ◽  
New Approach ◽  
Biometric Systems ◽  
Score Fusion ◽  
Face Biometrics ◽  
Match Score

In recent years, attacks on password databases have been carried out at an increasing rate, with significant success. Thus, a new approach is needed to prove one's claim to identity instead of relying on a password. In this paper, we investigate the use of biometric match scores for the purpose of verification. Our work was performed using the BSSR1 multimodal match score biometric dataset, which contains match scores from face and fingerprint biometric systems. We investigated the use of match scores as a feature vector, and performed Simple Sum and Product Rule fusion of match scores. The results we obtained demonstrated that the use of match scores for verification purposes can be achieved to give a result that is highly accurate.

Sign in / Sign up

Export Citation Format

Share Document