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Three Dimensional Face And Finger Biometrics
2004
Zenodo
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is computed over all three fingers) are shown. ...
CONCLUSIONS In this paper, we have described two classes of 3D biometrics: face (which has a decade of history and now is appearing in fielded systems) and finger (which, to our knowledge, has not been ...
doi:10.5281/zenodo.38702
fatcat:pqy2dqxlpfcrnev5h74tmebi4m
Decision Fusion based Person Identification System using Fingerprints and Facial Image with Template Matching
2018
Asian Journal of Computer and Information Systems
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In this research, it has been developed a prototype biometric system which integrates facial images and fingerprints. ...
The system overcomes the limitations of face recognition systems as well as fingerprint recognition systems. ...
Choice and number of biometric indicators: The proposed system uses three biometric (facial image and fingerprint) indicator to identify a person. ii. ...
doi:10.24203/ajcis.v6i3.5317
fatcat:bfl6c4ghrbbzdpvnbyrxeaawo4
Biometrics: Going 3D
2022
Sensors
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The face is further categorized into facial, ear, iris and skull, while the hand is divided into fingerprint, finger vein and palm. ...
Three main categories of 3D biometrics were identified. These were face, hand and gait. The corresponding percentages for these categories were 74.07%, 20.37% and 5.56%, respectively. ...
Acknowledgments: This work was supported by the MPhil program "Advanced Technologies in Informatics and Computers", hosted by the Department of Computer Science, International Hellenic University, Kavala ...
doi:10.3390/s22176364
pmid:36080821
pmcid:PMC9460341
fatcat:ixfndxuqjrdk3p4x6d25auxida
Multimodal Biometrics Based on Fingerprint and Finger Vein
2014
Research Journal of Applied Sciences Engineering and Technology
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This study considers multimodal biometrics based on fingerprint and finger veins. ...
Gabor features are extracted from finger vein using Gabor filter with orientation of 0, 15, 45, 60 and 75°, respectively. ...
Face trait builds GWNs based features while LBP was used for finger print trait. ...
doi:10.19026/rjaset.8.964
fatcat:i6qmizoqv5bavoupdi674eryti
Information Fusion in Biometrics
[chapter]
2001
Lecture Notes in Computer Science
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Experimental results on combining three biometric modalities (face, fingerprint and hand geometry) are presented. ...
User verification systems that use a single biometric indicator often have to contend with noisy sensor data, restricted degrees of freedom, non-universality of the biometric trait and unacceptable error ...
Face verification Face verification involves extracting a feature set from a two-dimensional image of the userÕs face and matching it with the template stored in the database. ...
doi:10.1007/3-540-45344-x_52
fatcat:vrux6ntqvbhlbakkasfesxysr4
Information fusion in biometrics
2003
Pattern Recognition Letters
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Experimental results on combining three biometric modalities (face, fingerprint and hand geometry) are presented. ...
User verification systems that use a single biometric indicator often have to contend with noisy sensor data, restricted degrees of freedom, non-universality of the biometric trait and unacceptable error ...
Face verification Face verification involves extracting a feature set from a two-dimensional image of the userÕs face and matching it with the template stored in the database. ...
doi:10.1016/s0167-8655(03)00079-5
fatcat:2g3yqzec7zgjvlxnw5stk73hme
An Efficient Human Identification through MultiModal Biometric System
2016
Brazilian Archives of Biology and Technology
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In this paper, a multimodal biometrics authentication is proposed by combining face, iris and finger features. ...
It is observed that, the combination of face, fingerprint and iris gives better performance in terms of accuracy, False Acceptance Rate, False Rejection Rate with minimum computation time. ...
Muhammad et.al (2011) proposed a multimodal biometric system using Face and Finger Veins. They used LDA methodology for dimensionality reduction. ...
doi:10.1590/1678-4324-2016161055
fatcat:ifmw3zkt4jcxhnaxdsy3hllpse
From Noise to Feature: Exploiting Intensity Distribution as a Novel Soft Biometric Trait for Finger Vein Recognition
2018
IEEE Transactions on Information Forensics and Security
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2021 pre-print arXiv:2112.07931v1 fatcat:ytd427tzyvf2lc3rj7hmefkpre
Then, two finger vein background layer extraction algorithms and three soft biometric trait extraction algorithms are proposed for intensity distribution feature extraction. ...
A series of rigorous contrast experiments on three open-access databases demonstrates that our proposed method is feasible and effective for finger vein recognition. ...
Traditionally, the fingerprint, face, iris, gait, voice, and finger vein are regarded as "hard" biometrics. ...
doi:10.1109/tifs.2018.2866330
fatcat:iwn7bfpbdrb4lgt6c2zbg7rgny
A Comparative Study of Biometric Technologies with Reference to Human Interface
2011
International Journal of Computer Applications
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Biometric systems that are currently available today examine fingerprints, handprints, iris and retina patterns, and face. ...
Over the next few years, the use of biometrics will continue to grow and become much more commonplace. ...
Hand Geometry When measuring hand geometry biometrics, three-dimensional image of the hand is taken and the shape and length of fingers and knuckles are measured. ...
doi:10.5120/1842-2493
fatcat:xi3yu6ow4rhnla6mwrjno3ui3e
A Hand Gesture-Based Method for Biometric Authentication
[chapter]
2018
Lecture Notes in Computer Science
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Using the motions of fingertips and finger joints as biometric data, the method improves the performance of authentication. Also, we propose seven 3D gestures that can be classified into three types. ...
As an alternative to passwords, biometric authentication, such as fingerprint authentication and face recognition-based authentication, is becoming more widely used. ...
We used, as biometric data, timed-based sequences of 3D positions of fingertips and finger joints. Also, we proposed seven 3D hand gestures that are classified into three types. ...
doi:10.1007/978-3-319-91238-7_43
fatcat:xhk3u6iujfgfxmezsfur4vsjdy
Cryptographic Algorithm based Feature Level Fusion of Fingerprint and Iris in a Multi-Biometric Recognition System
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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Biometric Recognition is based on the anatomical and behavior attributes of the individuals. Multibiometric is the combination of various biometrics like Fingerprint, Iris, and Face, Fingervein etc. ...
In this paper bio cryptosystem is proposed to improve the security of multimodal frameworks by producing the biocrypto key from Finger print and iris. ...
Past multimodal biometric frameworks dependent on face and iris recognition have utilized face and iris features [8, 9] . ...
doi:10.35940/ijitee.b6542.129219
fatcat:5ikkrqtk2jeilnmwmvpwjerwja
Exploring soft biometric trait with finger vein recognition
2014
Neurocomputing
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Finally, three frameworks are developed to conduct the combination of the width measurement and finger vein pattern, i.e., the fusion framework, the filter framework and the hybrid framework. ...
We perform rigorous experiments both on the open and self-built finger vein databases, and experimental results illustrate that soft biometric trait can make promising improvement of finger vein recognition ...
biometrics such as face, fingerprint, etc.. ...
doi:10.1016/j.neucom.2013.12.029
fatcat:grqsq2lovbhtlnbi5jogj6m6sm
Efficient Image Retrieval Techniques for Multi Biometric Images to Improve Biometric Authentication
2020
International journal of recent technology and engineering
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The proposed multi model biometrics system recognizes the human based on physical traits like iris, finger- print, faces and palm- print to obtain better retrieval accuracy, precision and retrieval speed ...
In physical, recognition of the human features like iris, face, finger-prints and palm print are normally used to improve the security and proper authentication. ...
Figure 3 3 fusion of different biometrics using different indexing techniques. Initially, Iris and Finger print features are fused. Then face and palm print features are fused. ...
doi:10.35940/ijrte.e6694.018520
fatcat:g27jt5pd3rhyrklgxuppjy6gu4
A Robust Multimodal Biometric System VIA Multiple Svms
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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This paper includes a robust multimodal biometric authentication system that integrates FKP (Finger-Knuckle Print), face and fingerprint at matching score level fusion using multiple parallel Support Vector ...
Every possible combination of three modalities (FKP, face and fingerprint) are taken into consideration and all combinations have a corresponding SVM to fuse the matching scores and produce the final score ...
Feature Set Extraction of Biometric Modalities Sensor collects the initial raw sample of three modalities (finger print, face and finger knuckle print), and an appropriate technique is carried out to extract ...
doi:10.35940/ijitee.k1042.09811s19
fatcat:bisnad3move2vltzymdn3ubuni
Convolutional Neural Network Based Multimodal Biometric Human Authentication using Face, Palm Veins and Fingerprint
2020
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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In propose system, multi layer Convolutional Neural Network (CNN) is applied to multimodal biometric human authentication using face, palm vein and fingerprints to increase the robustness of system. ...
For the evaluation of system self developed face, palm vein and fingerprint database having 4,500 images are used. ...
A finger multimodal biometric using three finger traits such as fingerprint, finger knuckle point and finger vein using graph fusion method [22] . ...
doi:10.35940/ijitee.c8467.019320
fatcat:myivrdtwavbyjeyqlkkssofcwa
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