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Feature Level fusion based on Conical Correlation Analysis and Discriminant Correlation Analysis for Palm Print and Hand Vein
2018
International Journal of Computer Applications
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In this paper, we present Discriminant Correlation Analysis (DCA), a feature level fusion technique that incorporates the class associations into the correlation analysis of the feature sets. ...
Information fusion is a key step in multimodal biometric systems. ...
which provides a constructive feature fusion model for real time applications in pattern recognition. ...
doi:10.5120/ijca2018917615
fatcat:y67ty3beszhibahvrhgqjz2i2i
Discriminant correlation analysis for feature level fusion with application to multimodal biometrics
2016
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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In this paper, we present Discriminant Correlation Analysis (DCA), a feature level fusion technique that incorporates the class associations in correlation analysis of the feature sets. ...
These characteristics make DCA an effective feature fusion tool for pattern recognition applications. Moreover, DCA is computationally efficient and can be employed in real-time applications. ...
doi:10.1109/icassp.2016.7472000
dblp:conf/icassp/HaghighatAA16
fatcat:5nmox63oajeqxowwlrrbu7r3xm
ANALYSIS OF SPOOFING ROBUSTNESS IN A MULTIMODAL BIOMETRIC SYSTEM
2017
International Journal of Advanced Research in Computer Science
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In this paper, face and fingerprint are the two biometrics used to build multibiometric system. Here, fusion of two modalities is done at matching score level. ...
Multimodal biometric system overcome all these limitations by presenting multiple evidences of single biometric trait due to which spoofing of these simultaneously become more difficult for an imposter ...
Fusion at the match score level has been adequately studied in the [8] , [9] , [10] ,[11] , [12] and is considered most robust level of fusion in multimodal biometric systems, due to ease in procuring ...
doi:10.26483/ijarcs.v8i7.4351
fatcat:lprj334kiraa5gccts3ievrtcq
Bimodal Multi-feature Fusion based on Quaternion Fisher Discriminant Analysis
2016
Journal of Information Hiding and Multimedia Signal Processing
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Along with other fusion level of multimodal biometrics, feature level can reduce the redundant information to avoid calculation consumption, and simultaneously acquire the discriminative information to ...
Because of its higher reliability, wider applicability and stronger security, multimodal biometrics has become a polar research direction of biometric recognition and attracts more and more research groups ...
According to the fusion location, multimodal biometric system has four fusion levels: pixel level, feature level, matching score level and decision level. ...
dblp:journals/jihmsp/WangCMT16
fatcat:oy3vqnxqjfcq7n2s44ex3a44km
A Short Review of Multimodal Biometric Recognition Systems
2017
Journal of Biometrics & Biostatistics
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They proposed a discriminant correlation analysis (DCA), a new technique of feature level fusion that integrates the class associations into the correlation analysis of the feature sets. ...
This low computational attribute can be modelled for real-time applications such as performing various complex biometric databases. ...
doi:10.4172/2155-6180.1000355
fatcat:ifjoqj2bwfbrtapebvc4v5hgoq
Analysis of Multi-modal Biometrics System for Gender Classification Using Face, Iris and Fingerprint Images
2019
International Journal of Image Graphics and Signal Processing
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In the proposed work, feature level fusion is considered to obtain robustness in gender determination; and an accuracy of 99.8% was achieved on homologous multimodal biometric database SDUMLA-HMT (Group ...
The results demonstrate that the feature level fusion of Multimodal Biometric system greatly improves the performance of gender classification and our approach outperforms the state-of-the-art techniques ...
From the literature, it is observed that there are different types of fusion levels they are; match score level, sensor level, feature level and decision level fusions. ...
doi:10.5815/ijigsp.2019.05.04
fatcat:nd6ph2wcijfwxjiff2iduxkw3q
Bi Modal Person Identification System
2013
International Journal of Machine Learning and Computing
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The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing principal component analysis and Fisher's linear Discriminant methods for individual matcher's ...
identity authentication and utilizes the novel feature fusion method to consolidate the results obtained from different biometric matchers. ...
[14] , proposed a feature fusion combined with 2D fisher linear Discriminant analysis for face and iris images. Maruf et al. ...
doi:10.7763/ijmlc.2013.v3.299
fatcat:btecgopo55hx5cy2dhbh3xrtbe
Deep multimodal biometric recognition using contourlet derivative weighted rank fusion with human face, fingerprint and iris images
2019
Automatika
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Weighted Rank Level Fusion is applied to the extracted multimodal features, that efficiently combine the biometric matching scores from several modalities (i.e. face, fingerprint and iris). ...
This paper explains a deep multimodal biometric system for human recognition using three traits, face, fingerprint and iris. ...
Impact of computational time The for Multi-Modal Recognition [1] and Discriminant Correlation Analysis (DCA) [2] , the computational time involved for human recognition is simplified as given below. ...
doi:10.1080/00051144.2019.1565681
fatcat:ziqkw7iw6veabakdsoo5j7vh3i
A Proposed Integrated Human Recognition for Security Reassurance
2015
American Journal of Applied Sciences
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In addition, two fusion strategies namely, score-level and decision-level are presented using robust algorithms. ...
For this reason, researchers pay great attention to the more advanced biometrics (referred to as multimodal biometrics). ...
The corresponding author thanks the Kano State Government Nigeria, for providing the scholarship. ...
doi:10.3844/ajassp.2015.155.165
fatcat:xfxak6jzjzdghnrtytvvoegfri
Real-Time Multimodal Biometric Authentication of Human Using Face Feature Analysis
2021
Computers Materials & Continua
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Biometrics combines the physiological and behavioral qualities of an individual to validate their character in real-time. ...
Scale Invariant Feature Transform (SIFT) and Speeded-up Robust Features (SURF) are employed for face recognition. ...
Funding Statement: The authors received no specific funding for this study.
Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study. ...
doi:10.32604/cmc.2021.015466
fatcat:ia4m3zf26zf3xjkmvvx7vj2bne
A Comparative Performance Analysis of Multimodal-Multialgorithm System Framework Based on Rank Level Fusion
2020
International journal of recent technology and engineering
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This paper gives a comparative analysis of multi-algorithm and multimodal system framework based on rank level fusion. ...
The Unimodal biometric framework have various fundamental issues, for example, intra-class alteration, noisy data, failure-to-enroll, spoofing attacks, unacceptable error rate and non-universality. ...
Biometrics features contain more valuable information than match score and for this reason feature level fusion provide better recognition capabilities than the rest fusion methods, yet, it is hard to ...
doi:10.35940/ijrte.b3890.079220
fatcat:ovrvvjbfdjf6nfz4e6p4zphufa
Multi Modal Biometric System: A Review on Recognition Method
2017
International Journal of Engineering Research and
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Literature reviews of the most recent multimodal biometric human recognition techniques are presented. ...
In this Review paper, it is intended to summarize and compare the biometric recognition for human identification. ...
The score level fusion of client specific linear discriminant analysis (CSLDA) for face recognition and fusion of face result and finger veins result is performed. ...
doi:10.17577/ijertv6is050102
fatcat:z3u632ry5fgbbfcivesokd7ttu
Face-Palm Identication System on Feature Level Fusion based on CCA
2013
Journal of Information Hiding and Multimedia Signal Processing
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In this paper, we propose an efficient feature-level fusion algorithm for face and palm. ...
We extract the features of face and palm by principal component analysis(PCA), and then use the canonical correlation analysis(CCA) to carry out feature fusion and get correlation characteristic features ...
Foundation (no.2012M511003), Project of Science and Technology of Heilongjiang Provincial Education Department(no.1252141 8), Youth Foundation of Heilongjiang University (no.201026), and Startup Fund for ...
dblp:journals/jihmsp/WangLSD13
fatcat:sjl7hr35hzhojgx4eukva5rno4
Confidence Based Rank Level Fusion for Multimodal Biometric Systems
[chapter]
2015
Lecture Notes in Computer Science
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An important aspect of a multimodal biometric system is the fusion of information from multiple biometric sources. ...
toward multimodal biometric systems. ...
Fisher's linear discriminant analysis is used for feature extraction of the face and ear. The Euclidean distance is used to compare features of the face and the ear biometric. ...
doi:10.1007/978-3-319-23192-1_18
fatcat:g5axb5lznzhcfhda7cvd4u2gom
Multimodal Biometric System by Feature Level Fusion of Palmprint and Fingerprint
2015
International Journal of Engineering Research and
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To overcome these drawbacks, multimodal biometrics emerged as new research area in the field of security. This paper focuses on the fusion of palmprint and fingerprint with feature level fusion. ...
Biometrics is the technology for measuring and analyzing human characteristics such as palmprint, fingerprint, voice, facial pattern, signature etc, for authentication purposes. ...
Monwar et.al [8] has discussed rank level fusion of face, ear and signature with principal component analysis and fisher's linear discriminant analysis for matching purpose. ...
doi:10.17577/ijertv4is070911
fatcat:njew3jgp6rddzn443vzne4yy4u
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