Contactless Multispectral Palm-Vein Recognition With Lightweight Convolutional Neural Network

Chen, Yung-Yao; Hsia, Chih-Hsien; Chen, Ping-Han

doi:10.1109/access.2021.3124631

Cited by 19 publications

(11 citation statements)

References 48 publications

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“…Chen et al. utilised CNN for palm vein recognition in [ 30 ]. Although the paper focuses specifically on palm vein recognition, the same concepts apply to wrist vein recognition, especially as the CNN is utilised after the ROI segmentation.…”

Section: Literature Reviewmentioning

confidence: 99%

Deep Learning-Based Wrist Vascular Biometric Recognition

Marattukalam

Abdulla

Cole

et al. 2023

Sensors

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The need for contactless vascular biometric systems has significantly increased. In recent years, deep learning has proven to be efficient for vein segmentation and matching. Palm and finger vein biometrics are well researched; however, research on wrist vein biometrics is limited. Wrist vein biometrics is promising due to it not having finger or palm patterns on the skin surface making the image acquisition process easier. This paper presents a deep learning-based novel low-cost end-to-end contactless wrist vein biometric recognition system. FYO wrist vein dataset was used to train a novel U-Net CNN structure to extract and segment wrist vein patterns effectively. The extracted images were evaluated to have a Dice Coefficient of 0.723. A CNN and Siamese Neural Network were implemented to match wrist vein images obtaining the highest F1-score of 84.7%. The average matching time is less than 3 s on a Raspberry Pi. All the subsystems were integrated with the help of a designed GUI to form a functional end-to-end deep learning-based wrist biometric recognition system.

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Section: Literature Reviewmentioning

confidence: 99%

Deep Learning-Based Wrist Vascular Biometric Recognition

Marattukalam

Abdulla

Cole

et al. 2023

Sensors

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“…Other studies use a convolutional neural network (CNN) to extract and categorize texture features for finger-vein biometrics. CNNs are highly effective but a previous study [3,4] proposed an identification process that is slower because the system must process more samples for DL.…”

Section: Review Of Literaturementioning

confidence: 99%

“…As the demand for privacy, security and convenience increases, biometrics have become increasingly popular as a fast and simple identification process that offers security, reliability, and accuracy. Its convenience also allows for safe monitoring and system management and integration [3,4]. Biometric characteristics are universal, permanent, distinctive and collectable [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

“…Each of these characteristics are used for biometric analysis but internal characteristics allow more accurate and secure identification. Internal characteristics that involve vessels such as finger-veins beneath the skin are not prone to wear or interference from external staining, water, light or other environmental variables that undermine identification [3,4]. External characteristics are more easily counterfeited and affected by an external environment, so they are less suited to biometrics.…”

Section: Introductionmentioning

confidence: 99%

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A New Enhancement Edge Detection of Finger-Vein Identification for Carputer System

Hsia

Yang

Wang³

et al. 2022

Applied Sciences

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Developments in multimedia and mobile communication technologies and in mobilized, personalized information security has benefitted various sectors of society, as traditional identification technologies are often complicated. In response to the sharing economy and the intellectualization of automotive electronics, major automobile companies are using biometric recognition to enhance the safety, uniqueness, and convenience of their vehicles. This study uses a deep learning-based finger-vein identification system for carputer systems. The proposed enhancement edge detection adapts to the detected fingers’ rotational and translational movements and to interference from external light and other environmental factors. This study also determines the effect of preprocessing methods on the system’s effectiveness. The experimental results demonstrate that the proposed system allows more accurate identification of 99.1% and 98.1% in various environments, using the FV-USM and SDUMLA-HMT public datasets. As results, the contribution of system is high accuracy and stability for more sanitary, contactless applications makes it eminently suited for use during the COVID-19 pandemic.

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“…Personalized Offers like in AI and ML algorithms can analyse customer data to provide personalized offers and discounts based on the customer's preferences, purchase history, and behaviour. This can help businesses improve customer loyalty and increase sales [14].…”

Section: Introductionmentioning

confidence: 99%

Payments With Palm Using Ai and Ml Algorithms

2023

IRJMETS

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Payments has changed drastically over decades talking from barter system to using currencies. So over the past few years we are able to observe many changes in the digital payments and many modes to pay take for instance apple pay we can use either phone, card else smart gadgets like apple watches to make payments and now we are taking this change to the next level and introducing palm payments and this is the future of payments [1].The proposed system for palm payments is used to make payments using palm lines as every ones palm lines are different we will be using lidar for scanning line movements and using AI and ML algorithms to process accurate results [2]. So we will be having checkout page as we generally see in any of the websites and usually we select either debit else credit card and PayPal and some digital payment modes but in our case we will be seeing palm symbol which indicates palm payments which is secure and fastest means of payment [3]. The system also checks weather it is hand is original else it's a picture and also dead or alive or any suspicious activity going on. if anything goes wrong it also enables two factor authentication for security purpose it may include either OTP for mobile else security question which is safest way to make transaction. So in order to use this feature user has to enroll himself in palm payments which is one time enrollment and can be used for life time and has some age limitations (Pandey, 2021) Hence, the proposed system can exclusively reduce the time for payments it is slowly expanding in metro cities in united states and amazon has started trials in some of the big cities like new York slowly it is getting recognized and soon it may become effective and efficient way of payments.

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Contactless Multispectral Palm-Vein Recognition With Lightweight Convolutional Neural Network

Abstract: Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.

Cited by 19 publications

References 48 publications

Deep Learning-Based Wrist Vascular Biometric Recognition

Deep Learning-Based Wrist Vascular Biometric Recognition

A New Enhancement Edge Detection of Finger-Vein Identification for Carputer System

Payments With Palm Using Ai and Ml Algorithms

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