3D ultrasound palm vein recognition through the centroid method for biometric purposes

Santis, Michele De; Agnelli, S.; Nardiello, Donatella; Iula, Antonio

doi:10.1109/ultsym.2017.8091946

Cited by 9 publications

(6 citation statements)

References 11 publications

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“…The proposed approach has the further merit of being able to automatically detect the liveness of the sample by checking vein pulsing during image acquisition, which makes it very difficult to spoof. Furthermore, the same volumetric image can be exploited for extracting other 3-D palmprint features through curvature methods [34] as well as other features than palmprint like inner hand geometry [66], hand geometry [67], [68] and vein pattern [69], [70], implementing in this way a hand-based multimodal system, which is expected to improve the overall performances of the system.…”

Section: Discussionmentioning

confidence: 99%

A Feasible 3D Ultrasound Palmprint Recognition System for Secure Access Control Applications

Iula

Micucci

2021

IEEE Access

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Biometric recognition systems based on 3D palmprint captured with optical technology have been widely investigated in the last decade; however, they can provide information about the external skin surface only. This limit can be overcome by Ultrasound, which allows gaining information on the depth of palm lines and can verify the liveness of the sample, making the recognition systems very hard to fake. In this work, a feasible palmprint recognition system based on 3D ultrasound images is proposed. Unlike previous wet setups, the coupling between probe and human is realized through a gel pad, which permits a comfortable and precise positioning of the hand by the user. Collected 3D images are processed to generate 2D palmprint images at various under-skin depths. 2D features are then extracted from these images, experimenting with different procedures, and are merged to define a 3D template that contains lines' depth information. Recognition performances were evaluated by performing verification and identification experiments on a home-made database composed of 423 samples from 55 volunteers. An EER rate of 0.36% and an identification accuracy of 100% are obtained. The suitability of the proposed system in secure access control applications is finally discussed.

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Section: Discussionmentioning

confidence: 99%

A Feasible 3D Ultrasound Palmprint Recognition System for Secure Access Control Applications

Iula

Micucci

2021

IEEE Access

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“…The next operation is binarization. In previous works [37,38], a global threshold was set based on heuristic considerations. However, this approach is suitable only if images under analysis have more or less the same characteristics in terms of illumination and contrast.…”

Section: Feature Extractionmentioning

confidence: 99%

3D Vascular Pattern Extraction from Grayscale Volumetric Ultrasound Images for Biometric Recognition Purposes

Iula

Vizzuso

2022

Applied Sciences

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Recognition systems based on palm veins are gaining increasing attention as they are highly distinctive and very hard to counterfeit. Most popular systems are based on infrared radiation; they have the merit to be contactless but can provide only 2D patterns. Conversely, 3D patterns can be achieved with Doppler or photoacoustic methods, but these approaches require too long of an acquisition time. In this work, a method for extracting 3D vascular patterns from conventional grayscale volumetric images of the human hand, which can be collected in a short time, is proposed for the first time. It is based on the detection of low-brightness areas in B-mode images. Centroids of these areas in successive B-mode images are then linked through a minimum distance criterion. Preliminary verification and identification results, carried out on a database previously established for extracting 3D palmprint features, demonstrated good recognition performances: EER = 2%, ROC AUC = 99.92%, and an identification rate of 100%. As further merit, 3D vein pattern features can be fused to 3D palmprint features to implement a costless multimodal recognition system.

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“…Blue illumination enhances the skin surface structure, whereas far‐red and infra‐red mainly show the vein structure. Antonio [21] used a commercial ultrasound imaging machine to capture the 3D palm vein pattern. Wang [22] gets deep information of the palm vessel through a 3‐D image of palm vasculature.…”

Section: Palm Vein Image Acquisitionmentioning

confidence: 99%

Review of palm vein recognition

Elliott

Lin

et al. 2019

IET biom.

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As a new research focus in biometrics, palm vein recognition has attracted people's attention because of high security, liveness-detection, user acceptability and convenience. Palm vein recognition exhibits high security, as it uses the network of blood vessels underneath palm skin for recognition. As palm vein is interior biological information of the body, vein patterns are much harder for intruders to copy compared to other biometric features. Palm vein is mostly invisible to the human eyes; they are commonly captured under near-infrared light. Under its natural state, the veins of the palm are concealed naturally and, for most of time people's hands are in the gesture of half fist. This study presents a comprehensive overview of recent research progress of palm vein recognition, from the basic background knowledge to data acquisition, public database, preprocessing, feature extraction and matching. In addition, the study focuses on palm vein-related fusion. Ultimately, the authors discuss the challenges and future perspectives in palm vein recognition for further works.

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3D ultrasound palm vein recognition through the centroid method for biometric purposes

Cited by 9 publications

References 11 publications

A Feasible 3D Ultrasound Palmprint Recognition System for Secure Access Control Applications

A Feasible 3D Ultrasound Palmprint Recognition System for Secure Access Control Applications

3D Vascular Pattern Extraction from Grayscale Volumetric Ultrasound Images for Biometric Recognition Purposes

Review of palm vein recognition

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