Contact-Less Palm&amp;#x002F;Finger Vein Biometrics

Sierro, Alexandre; Ferrez, Pierre W.; Roduit, Pierre

doi:10.1109/biosig.2015.7314596

Cited by 18 publications

(11 citation statements)

References 8 publications

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“…Kim et al [10] arrived at an EER of 3.6% for their NIR laser based contactless acquisition set-up. Sierro et al [9] did not present any performance evaluation of their dataset. None of the mentioned authors disclosed their dataset, so their results are not reproducible.…”

Section: Discussionmentioning

confidence: 99%

“…Due to the challenges and problems with contactless acquisition, there are only a few contactless finger vein capturing devices proposed in research. One of these devices is a mobile finger vein scanner for Android proposed by Sierro et al [9]. Their prototype device captures contactless palmar finger vein images using reflected light.…”

Section: Introductionmentioning

confidence: 99%

“…The CCD camera is located at the bottom of the device and the LEDs in different wavelength spectra are located around the camera. Sierro et al [9] also proposed two contactless palm vein capturing device prototypes. Both are using the reflected light set-up and are equipped with ultrasonic sensors to measure the distance between the camera and the hand.…”

Section: Introductionmentioning

confidence: 99%

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Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset

Kauba

Prommegger

Uhl

2019

Sensors

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Vascular pattern based biometric recognition is gaining more and more attention, with a trend towards contactless acquisition. An important requirement for conducting research in vascular pattern recognition are available datasets. These datasets can be established using a suitable biometric capturing device. A sophisticated capturing device design is important for good image quality and, furthermore, at a decent recognition rate. We propose a novel contactless capturing device design, including technical details of its individual parts. Our capturing device is suitable for finger and hand vein image acquisition and is able to acquire palmar finger vein images using light transmission as well as palmar hand vein images using reflected light. An experimental evaluation using several well-established vein recognition schemes on a dataset acquired with the proposed capturing device confirms its good image quality and competitive recognition performance. This challenging dataset, which is one of the first publicly available contactless finger and hand vein datasets, is published as well.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset

Kauba

Prommegger

Uhl

2019

Sensors

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“…It is important to note that this work is based on a custom sensor device which is able to apply reflected light as well as transillumination imaging [72]. Another reflected light palm vein sensor prototype is presented in [238]. After a scaling normalisation of the RoI, [172,173] apply LBP and LDP for local feature encoding.…”

Section: Palm Vein Recognition Toolchainmentioning

confidence: 99%

“…In any case, external NIR illumination is used, image acquisition is done either with a smartphone (with NIR-blocking filter in place) or an external night-vision webcam used as a smartphone plug-in. Contrasting to this simple solution, a custom-built plug-on finger vein acquisition device [239] based on reflection-based imaging has been developed. Experimentation reveals rather low contrast, especially in difficult lighting conditions.…”

Section: Hand-based Vascular Traitsmentioning

confidence: 99%

State of the Art in Vascular Biometrics

Uhl

2019

Handbook of Vascular Biometrics

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The investigation of vascular biometric traits has become increasingly popular during the last years. This book chapter provides a comprehensive discussion of the respective state of the art, covering hand-oriented techniques (finger vein, palm vein, (dorsal) hand vein and wrist vein recognition) as well as eye-oriented techniques (retina and sclera recognition). We discuss commercial sensors and systems, major algorithmic approaches in the recognition toolchain, available datasets, public competitions and open-source software, template protection schemes, presentation attack(s) (detection), sample quality assessment, mobile acquisition and acquisition on the move, and finally eventual disease impact on recognition and template privacy issues.

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Vein detection with near‐infrared organic photodetectors for biometric authentication

et al. 2020

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We combine a low dark current and high‐detectivity near‐infrared (NIR)‐sensitive organic photodetector with a high‐resolution 508 pixels per inch (ppi) oxide thin‐film transistor (TFT) backplane to create a large‐area thin NIR detector, using processes that are compatible with flat‐panel display fabrication. The detector is characterized showing high uniformity and linearity. With the use of a NIR light source, the detector is capable of imaging the (pattern of) veins under the skin in reflection, leading to improved biometric authentication.

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Contact-Less Palm/Finger Vein Biometrics

Cited by 18 publications

References 8 publications

Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset

Combined Fully Contactless Finger and Hand Vein Capturing Device with a Corresponding Dataset

State of the Art in Vascular Biometrics

Vein detection with near‐infrared organic photodetectors for biometric authentication

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