System for multimodal biometric recognition based on finger knuckle and finger vein using feature‐level fusion and k‐support vector machine classifier

Veluchamy, S.; Karlmarx, L. R.

doi:10.1049/iet-bmt.2016.0112

Cited by 73 publications

(38 citation statements)

References 22 publications

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“…In multimodal biometric recognition system, repeated line tracking technique was also implemented to obtain feature extraction. In Reference [65], the repeated line tracking approach with feature-level fusion using fractional firefly (FFF) optimization was employed to extract features from finger knuckle and finger vein images.…”

Section: Vein-based Methodsmentioning

confidence: 99%

“…Conventional finger vein identification approach uses the distance-based matching technique, while by machine learning techniques finger vein recognition can employ classifier-based matching technique. Classifier-based matching techniques were employed by References [29,49,61,65,85,86,99,100] for finger vein recognition systems. Table 3 summarizes the conventional finger vein recognition approaches, and Table 4 shows the machine learning algorithms-based FVR methods.…”

Section: Matchingmentioning

confidence: 99%

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A Systematic Review of Finger Vein Recognition Techniques

Han-gang²,

et al. 2018

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Biometric identification is the study of physiological and behavioral attributes of an individual to overcome security problems. Finger vein recognition is a biometric technique used to analyze finger vein patterns of persons for proper authentication. This paper presents a detailed review on finger vein recognition algorithms. Such tools include image acquisition, preprocessing, feature extraction and matching methods to extract and analyze object patterns. In addition, we list some novel findings after the critical comparative analysis of the highlighted techniques. The comparative studies indicate that the accuracy of finger vein identification methods is up to the mark.

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Section: Vein-based Methodsmentioning

confidence: 99%

Section: Matchingmentioning

confidence: 99%

A Systematic Review of Finger Vein Recognition Techniques

Han-gang²,

et al. 2018

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“…Veluchamy et al [1] proposed a multimodal biometric system based on the fusion of finger knuckle and finger vein features by making use of novel technique fractional firefly (FFF) optimization method. To extract the features from finger knuckle and finger vein images line tracking method is adopted.…”

Section: Related Workmentioning

confidence: 99%

“…Recent survey as shown that in today's real world most of the Biometric systems are unimodal systems which depends on one source of information for authentication [1]. Some of the widely known biometrics adopted for human identifications are single fingerprint, iris, face, voice, and DNApalmprint and hand vein.…”

Section: Introductionmentioning

confidence: 99%

Feature Level fusion based on Conical Correlation Analysis and Discriminant Correlation Analysis for Palm Print and Hand Vein

Rangappa¹,

Naveena²,

K.³

et al. 2018

IJCA

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Information fusion is a key step in multimodal biometric systems. Fusion of information can occur at different levels of a recognition system, i.e., at the feature level, matching-score level, or decision level. However, feature level fusion is believed to be more effective owing to the fact that a feature set contains richer information about the input biometric data than the matching score or the output decision of a classifier. The goal of feature fusion for recognition is to combine relevant information from two or more feature vectors into a single one with more discriminative power than any of the input feature vectors. In pattern recognition problems, we are also interested in separating the classes. 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. DCA performs an effective feature fusion by maximizing the pairwise correlations across the two feature sets, and at the same time, eliminating the between-class correlations and restricting the correlations to be within the classes. Our proposed method can be used in pattern recognition applications for fusing features extracted from multiple modalities or combining different feature vectors extracted from a single modality. It is noteworthy that DCA is the first technique that considers class structure in feature fusion. Moreover, it has a very low computational complexity and it can be employed in real-time applications. Multiple sets of experiments performed on Palm print and Hand vein datasets, and using different feature extraction techniques.

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“…32 Some works combine the fusion of fingerprints-face features, 33,34 others fused face and iris biometrics. 35 Other interesting approaches are the fusion of finger knuckle and finger vein, 36 and many other combinations.…”

mentioning

confidence: 99%

Assessment of privacy and security perception of biometric technology case study of Kaduna state tertiary academic institutions

Olorunsola

Ogwueleka

Evwiekpaefe

2020

Security and Privacy

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Biometric authentication technology are being increasingly used for many applications. Since such technology requires high level human interaction, effective implementation and acceptability of such system depends on users' perception, particularly, in the area of system safety and privacy. This study was conducted using a survey design accomplished through the use of a descriptive rating, Likert‐type survey instrument. Quantitative data were collected from participants in four tertiary academic institutions and Statistical Package for Social Science version 23 was used for data analysis. The survey focuses on three universities and a polytechnic situated in Kaduna metropolis. Deliberate sampling technique was used in selecting the four academic institutions, stratified random sampling technique was used in administering the survey instrument to 50 respondents from each institutions. The survey sampled 200 participants. Result from the study revealed the importance of considering users' perception before the implementation of biometric system. Major factors that significantly influence perception in this study are users' knowledge of biometric system and gender. Furthermore, 99.5% of the respondents show that public enlightenment and formulation of appropriate legal guidelines to back the use of biometric information will instil confidence in users of biometric technology.

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System for multimodal biometric recognition based on finger knuckle and finger vein using feature‐level fusion and k‐support vector machine classifier

Cited by 73 publications

References 22 publications

A Systematic Review of Finger Vein Recognition Techniques

A Systematic Review of Finger Vein Recognition Techniques

Feature Level fusion based on Conical Correlation Analysis and Discriminant Correlation Analysis for Palm Print and Hand Vein

Assessment of privacy and security perception of biometric technology case study of Kaduna state tertiary academic institutions

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