Accurate palm vein recognition based on wavelet scattering and spectral regression kernel discriminant analysis

Elnasir, Selma; Shamsuddin, Siti Mariyam; Farokhi, Sajad

doi:10.1117/1.jei.24.1.013031

Cited by 6 publications

(3 citation statements)

References 29 publications

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“…For instance, it is established that about 2% of the targeted population find it difficult to scan their fingerprints and getting good quality fingerprint images from manual workers [29]. Likewise, face biometric recognition encounters difficulties such as noise, variations in pose and illumination [30], while iris and retina-based biometrics are inconvenient for users [14].…”

Section: Figure 1the Composition Of Biometrics Systemmentioning

confidence: 99%

Finger vein recognition techniques: a comprehensive review

Kolivand

Asadianfam

Akintoye

et al. 2023

Multimed Tools Appl

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This paper discusses a comprehensive review of the previous research in the field of the finger vein recognition system with a focus on finger vein enhancements and features extraction advances and shortcomings. It starts with a general introduction of the biometric system followed by detailed descriptions on finger vein identification, and its architecture archival of it, which includes image acquisition, preprocessing of the image, feature extraction, and vein matching. This study focuses on related work proposed by previous researchers, issues in the field that originated from the related work, and a discussion of each of the issues associated and the proposed solutions to each of them. Next a comprehensive discussion on the advances and shortcomings of the existing techniques based on the qualities, capturing device, database, and feature of that quality is presented.Accurate comparisons between existing techniques are presented as tables to make it easy for new researchers to come up with advances and drawbacks of each technique without spending time on all existing research in this area.

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Section: Figure 1the Composition Of Biometrics Systemmentioning

confidence: 99%

Finger vein recognition techniques: a comprehensive review

Kolivand

Asadianfam

Akintoye

et al. 2023

Multimed Tools Appl

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“…In particular, the Design Fiction will illustrate the use of Digital Signature (DS, e.g. pin, password) [17] [18], DFS [19] and Contactless Palm Vein Authentication (CPVA) [20] to authenticate (authorise) access to user identification transaction systems (UITS). The research project builds a simulation of an e-commerce application that will accept DS, DFS and CPVA access to a UITS, where in this case the UITS will be a simulated payment system, i.e.…”

Section: Research Backgroundmentioning

confidence: 99%

Contactless Palm Vein Authentication Security Technique for Better Adoption of e-Commerce in Developing Countries

Alabi

White

Beloff

2020

Advances in Intelligent Systems and Computing

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E-commerce has contributed immensely to the economies of developed countries and a factor in its success can be attributed to the adoption of e-commerce by their citizens. As such, it is perceived that ecommerce can also be an economic driver for developing countries. However, security has been identified as a major barrier that prevents citizens from adopting e-commerce in developing countries. Therefore, this paper examines Security Authentication Techniques (SAT), particularly Digital Signature (DS) and Digital Fingerprint Systems (DFS), including the limitations of these two security techniques, and then proposes Contactless Palm Vein Authentication (CPVA) as a potentially much better solution to increase adoption of e-commerce in developing countries. The architecture of this new CPVA technique is discussed in relation to Security, Privacy, Trust and Reliability. Participants are treated to a Design Fiction Documentary (DFD) and Design Fiction Simulation Experiment (DFSE) in our experimental design method to measure the potential Technology Acceptance (adoption) of the proposed CPVA technique over DS and DFS authentication techniques. The result of our pilot study indicates that citizens may be willing to adopt the proposed CPVA technique, which may increase their trust and likely adoption of more e-commerce applications. A larger main study is planned in the field in Nigeria starting January 2020.

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“…However, these systems still had a major challenge due to the iris images' complex texture. Furthermore, implementing iris-based systems was very costly and had high computational complexity [9,10]. According to all the aspects discussed, the researcher decided to introduce techniques that were not firstly subject to destruction and had the least changes.…”

Section: Introductionmentioning

confidence: 99%

Finger Vein Authentication Based on Wavelet Scattering Networks

Rehman¹,

Harouni²,

Omidiravesh³

et al. 2022

Computers, Materials &Amp; Continua

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Biometric-based authentication systems have attracted more attention than traditional authentication techniques such as passwords in the last two decades. Multiple biometrics such as fingerprint, palm, iris, palm vein and finger vein and other biometrics have been introduced. One of the challenges in biometrics is physical injury. Biometric of finger vein is of the biometrics least exposed to physical damage. Numerous methods have been proposed for authentication with the help of this biometric that suffer from weaknesses such as high computational complexity and low identification rate. This paper presents a novel method of scattering wavelet-based identity identification. Scattering wavelet extracts image features from Gabor wavelet filters in a structure similar to convolutional neural networks. What distinguishes this algorithm from other popular feature extraction methods such as deep learning methods, filter-based methods, statistical methods, etc., is that this algorithm has very high skill and accuracy in differentiating similar images but belongs to different classes, even when the image is subject to serious damage such as noise, angle changes or pixel location, this descriptor still generates feature vectors in a way that minimizes classifier error. This improves classification and authentication. The proposed method has been evaluated using two databases Finger Vein USM (FV-USM) and Homologous Multimodal biometrics Traits (SDUMLA-HMT). In addition to having reasonable computational complexity, it has recorded excellent identification rates in noise, rotation, and transmission challenges. At best, it has a 98.2% identification rate for the SDUMLA-HMT database and a 96.1% identification rate for the FV-USM database.

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Accurate palm vein recognition based on wavelet scattering and spectral regression kernel discriminant analysis

Cited by 6 publications

References 29 publications

Finger vein recognition techniques: a comprehensive review

Finger vein recognition techniques: a comprehensive review

Contactless Palm Vein Authentication Security Technique for Better Adoption of e-Commerce in Developing Countries

Finger Vein Authentication Based on Wavelet Scattering Networks

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