A Dynamic Biometric Authentication Algorithm for Near-Infrared Palm Vascular Patterns

Palma, David A.; Blanchini, Franco; Giordano, Giulia; Montessoro, Pier Luca

doi:10.1109/access.2020.3005460

Cited by 7 publications

(4 citation statements)

References 31 publications

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“…If either P a or P b is zero, the impulse noise is called unipolar. If neither probability is zero, and especially if they are approximately equal, impulse noise values will resemble salt-and-pepper grains randomly distributed over the image [ 44 ]. Therefore, in the case of the RGB colour space, such a noise is always independent, randomly distributed, and uncorrelated with respect to each colour component.…”

Section: Resultsmentioning

confidence: 99%

A system-theoretic approach for image-based infectious plant disease severity estimation

2022

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The demand for high level of safety and superior quality in agricultural products is of prime concern. The introduction of new technologies for supporting crop management allows the efficiency and quality of production to be improved and, at the same time, reduces the environmental impact. Common strategies to disease control are mainly oriented on spraying pesticides uniformly over cropping areas at different times during the growth cycle. Even though these methodologies can be effective, they present a negative impact in ecological and economic terms, introducing new pests and elevating resistance of the pathogens. Therefore, consideration for new automatic and accurate along with inexpensive and efficient techniques for the detection and severity estimation of pathogenic diseases before proper control measures can be suggested is of great realistic significance and may reduce the likelihood of an infection spreading. In this work, we present a novel system-theoretic approach for leaf image-based automatic quantitative assessment of pathogenic disease severity regardless of disease type. The proposed method is based on a highly efficient and noise-rejecting positive non-linear dynamical system that recursively transforms the leaf image until only the symptomatic disease patterns are left. The proposed system does not require any training to automatically discover the discriminative features. The experimental setup allowed to assess the system ability to generalise symptoms detection beyond any previously seen conditions achieving excellent results. The main advantage of the approach relies in the robustness when dealing with low-resolution and noisy images. Indeed, an essential issue related to digital image processing is to effectively reduce noise from an image whilst keeping its features intact. The impact of noise is effectively reduced and does not affect the final result allowing the proposed system to ensure a high accuracy and reliability.

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Section: Resultsmentioning

confidence: 99%

A system-theoretic approach for image-based infectious plant disease severity estimation

2022

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“…Vascular patterns: This biometric trait has been largely investigated for its advantages over other features. In fact, the vascular pattern of the human body is unique to every individual, even between identical twins [8], remains steady during the course of a person's life, and lies underneath the human skin ensuring confidentiality and robustness to counterfeiting, as opposed to other intrinsic and extrinsic biometric traits that are more vulnerable to spoofing, thus leading to important security and privacy concerns [9]. To acquire the network structure of blood vessels underneath the human skin, a vascularbased recognition system uses near-infrared light to reflect or transmit images of blood vessels, since they are almost invisible in normal lighting conditions [10].…”

Section: Physiological/biological (Intrinsic) Human Characteristicsmentioning

confidence: 99%

Biometric-Based Human Recognition Systems: An Overview

Palma¹,

Montessoro²

2022

Recent Advances in Biometrics

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With the proliferation of automated systems for reliable and highly secure human authentication and identification, the importance of technological solutions in biometrics is growing along with security awareness. Indeed, conventional authentication methodologies, consisting of knowledge-based systems that make use of something you know (e.g., username and password) and token-based systems that make use of something you have (e.g., identification card), are not able to meet the strict requirements of reliable security applications. Conversely, biometric systems make use of behavioral (extrinsic) and/or physiological (intrinsic) human characteristics, overcoming the security issues affecting the conventional methods for personal authentication. This book chapter provides an overview of the most commonly used biometric traits along with their properties, the various biometric system operating modalities as well as various security aspects related to these systems. In particular, it will be discussed the different stages involved in a biometric recognition process and further discuss various threats that can be exploited to compromise the security of a biometric system. Finally, in order to evaluate the systems’ performance, metrics must be adopted. The most widely used metrics are, therefore, discussed in relation to the provided system accuracy and security, and applicability in real-world deployments.

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“…The former is mainly based on CCD cameras and contactless technique [ 8 , 9 , 10 ]: CCD cameras collect high-quality images but are limited by the bulkiness of the device, while contactless modality is highly useful for acceptability of users and reasons of personal hygiene, but it is not very reliable for low-quality images. Regarding the latter, both Near-Infrared (NIR) and Far-Infrared (FIR) radiation are used [ 11 , 12 ]. The principal limit of these technologies is their capability of providing information present only on the external skin surface.…”

Section: Introductionmentioning

confidence: 99%

Recognition Performance Analysis of a Multimodal Biometric System Based on the Fusion of 3D Ultrasound Hand-Geometry and Palmprint

Micucci

Iula

2023

Sensors

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Multimodal biometric systems are often used in a wide variety of applications where high security is required. Such systems show several merits in terms of universality and recognition rate compared to unimodal systems. Among several acquisition technologies, ultrasound bears great potential in high secure access applications because it allows the acquisition of 3D information about the human body and is able to verify liveness of the sample. In this work, recognition performances of a multimodal system obtained by fusing palmprint and hand-geometry 3D features, which are extracted from the same collected volumetric image, are extensively evaluated. Several fusion techniques based on the weighted score sum rule and on a wide variety of possible combinations of palmprint and hand geometry scores are experimented with. Recognition performances of the various methods are evaluated and compared through verification and identification experiments carried out on a homemade database employed in previous works. Verification results demonstrated that the fusion, in most cases, produces a noticeable improvement compared to unimodal systems: an EER value of 0.06% is achieved in at least five cases against values of 1.18% and 0.63% obtained in the best case for unimodal palmprint and hand geometry, respectively. The analysis also revealed that the best fusion results do not include any combination between the best scores of unimodal characteristics. Identification experiments, carried out for the methods that provided the best verification results, consistently demonstrated an identification rate of 100%, against 98% and 91% obtained in the best case for unimodal palmprint and hand geometry, respectively.

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A Dynamic Biometric Authentication Algorithm for Near-Infrared Palm Vascular Patterns

Abstract: The research leading to these results has been supported in part by the European Commission through the European Commission's S3 Operation (ESF/2014-2020 axis 3) within the "HEaD-Higher Education and Development" project (operation code 1619942002, funding channel 1420AFPLO1).

Cited by 7 publications

References 31 publications

A system-theoretic approach for image-based infectious plant disease severity estimation

A system-theoretic approach for image-based infectious plant disease severity estimation

Biometric-Based Human Recognition Systems: An Overview

Recognition Performance Analysis of a Multimodal Biometric System Based on the Fusion of 3D Ultrasound Hand-Geometry and Palmprint

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