Browsing Faculty Contributions by Subject "Biometrics"
Now showing items 1-12 of 12
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A comprehensive overview of feature representation for biometric recognition
( Springer , 2020 , Article)The performance of any biometric recognition system heavily dependents on finding a good and suitable feature representation space where observations from different classes are well separated. Unfortunately, finding this ... -
A multi-modal face and signature biometric authentication system using a max-of-scores based fusion
( Springer , 2012 , Conference Paper)Face and signature based multimodal biometric systems are often required in various areas, such as banking biometric systems and secured mobile phone operating systems, among others. Our system combines these two biometric ... -
An Ensemble Learning Method Based on Random Subspace Sampling for Palmprint Identification
( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)Palmprint recognition is an important and widely used biometric modality with high reliability, stability and user acceptability. In this paper we propose a simple and effective ensemble learning method for palmprint ... -
An improved palmprint recognition system using iris features
( Springer , 2013 , Article)This paper presents a bimodal biometric recognition system based on the extracted features of the human palmprint and iris using a new graph-based approach termed Fisher locality preserving projections (FLPP). This new ... -
Combining Fisher locality preserving projections and passband DCT for efficient palmprint recognition
( Elsevier B.V. , 2015 , Article)In this paper a new graph based approach referred to as Fisher Locality Preserving Projections (FLPP) is proposed for efficient palmprint recognition. The technique employs two graphs with the first being used to characterize ... -
EDITH : ECG Biometrics Aided by Deep Learning for Reliable Individual Authentication
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)In recent years, physiological signal-based authentication has shown great promises, for its inherent robustness against forgery. Electrocardiogram (ECG) signal, being the most widely studied biosignal, has also received ... -
Face Recognition in the Scrambled Domain via Salience-Aware Ensembles of Many Kernels
( Institute of Electrical and Electronics Engineers Inc. , 2016 , Article)With the rapid development of Internet-of-Things (IoT), face scrambling has been proposed for privacy protection during IoT-targeted image/video distribution. Consequently, in these IoT applications, biometric verification ... -
Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Electroencephalography (EEG) based biometric systems are gaining attention for their anti-spoofing capability but lack accuracy due to signal variability at different psychological and physiological conditions. On the other ... -
Off-line writer identification using multi-scale local binary patterns and SR-KDA
( IEEE , 2013 , Conference Paper)Writer identification is becoming an increasingly important research topic especially in forensic and biometric applications. This paper presents a novel method for performing offline write identification by using multi-scale ... -
Palmprint identification using an ensemble of sparse representations
( Institute of Electrical and Electronics Engineers Inc. , 2017 , Article)Among various palmprint identification methods proposed in the literature, sparse representation for classification (SRC) is very attractive offering high accuracy. Although SRC has good discriminative ability, its performance ... -
Robust biometric system using session invariant multimodal EEG and keystroke dynamics by the ensemble of self-ONNs
( Elsevier Ltd , 2022 , Article)Harnessing the inherent anti-spoofing quality from electroencephalogram (EEG) signals has become a potential field of research in recent years. Although several studies have been conducted, still there are some vital ... -
Unsupervised feature selection method for improved human gait recognition
( Institute of Electrical and Electronics Engineers Inc. , 2015 , Conference Paper)Gait recognition is an emerging biometric technology which aims to identify people purely through the analysis of the way they walk. The technology has attracted interest as a method of identification because it is ...