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Results of the proposed vascular pattern extraction method on PolyU (upper row) and CASIA (lower row) databases: (a) original ROI images, (b) boolean vascular pattern matrices, and (c) original ROI images overlapped with the extracted vascular patterns.
Source publication
In this paper we apply a novel approach to near-infrared subcutaneous palm vascular pattern authentication. The proposed method relies on a recursive algorithm based on a positive linear dynamical system whose evolution depends on the two matrices representing the vein patterns to be compared. The output of the system reaches a high value when a go...
Contexts in source publication
Context 1
... proposed feature extraction stage makes use of the following steps: 1) highlighting blood vessels by enhancing contrast and sharpness, 2) Laplacian of Gaussian, and 3) morphological operations. Figure 2 depicts the results of the proposed feature extraction algorithm. ...
Context 2
... an iterative thinning transformation is applied to reduce a foreground object to a minimal connected stroke preserving the topology [20], since the final vascular pattern image is homotopically equivalent to the input image. Figure 2 exemplifies the vascular pattern extraction method. ...
Citations
... ensuring the security of data transmission and storage. [12,13] A straightforward approach for achieving privacy in carpooling transactions could therefore be to make use of standard encryption algorithms like data encryption standard and advanced encryption standard. However, conventional ciphers still necessitate decryption before data can be compared, thus exposing sensitive information and compromising both the security of the system and the privacy of the individuals during this process. ...
Carpooling enables multiple users with similar travel habits to share rides, reducing vehicles on the road, leading to benefits such as lower fuel consumption, reduced traffic congestion, and lower environmental impact. However, carpooling also poses a challenge to the privacy of the users, as they may not want to reveal their location or route information to others. This research study delves into a cutting‐edge approach to address these privacy concerns by leveraging homomorphic encryption (HE) within the realm of carpooling services. The proposed solution makes use of a HE scheme that supports encrypted computation on real numbers, which is suitable for carpooling applications that involve distance and time calculations. The approach enables decision makers to perform efficient and accurate route matching over encrypted data, without disclosing their sensitive information about users, thus preserving the confidentiality of the data. The proposed system is evaluated through extensive experiments and simulations, demonstrating its effectiveness in terms of both security and privacy when the system operates in normal (ideal) and abnormal (under attack) conditions. Experimental results indicate that the proposed solution offers robust resistance to various attacks, including replay attacks and data exposure, providing a robust and privacy‐centric solution for carpooling services.
... The method employs a recursive algorithm as per a positive linear dynamical system to compare vein patterns, demonstrating strong noise-rejection and authentication capabilities even with corrupted images. Experiments on the PolyU and CASIA multi-spectral palmprint databases yielded very low EER: 2.341×10 -5 for PolyU and 1.081×10 -3 for CASIA [23]. A 2-D Gabor filter is utilized to extract local features from the palm vein patterns, and a new directional coding technique encodes these features as bit strings called Vein Codes. ...
... The intricate and highly personalised nature of the retina biometric trait makes it an ideal candidate for the application of cancelable template without any helper data. As retinal scans provide a wealth of information about an individual's identity, ensuring the confidentiality and integrity of this data is a crucial aspect [23]. ...
... The procedure starts with a pre-processing of the raw image, which conists of the selection and subsequent extraction of the green channel from the raw RGB image, as it provides the maximum contrast between exudates and the neighboring regions [62]. Hence, contrast and luminosity normalisation is applied to the extracted image I thorugh the following pixelwise procedure [23]: ...
... Ultimately, an iterative thinning transformation is applied to reduce the foreground object to a minimal connected stroke while preserving its topology. This ensures that the final vascular pattern image maintains its homotopic equivalence to the original input image [23]. ...
Securing personal information and data has become an imperative challenge, especially after the introduction of legal frameworks, such as, in Europe, the General Data Protection Regulation (GDPR). Conventional authentication methods, such as PINs and passwords, have demonstrated their vulnerabilities to various cyber threats, making it necessary the study of robust and reliable biometric authentication systems that can accurately verify an user’s identity. The human retina has demonstrated remarkable reliability as a biometric trait mainly because of its unique and stable patterns, even though the adoption of these systems gives rise to significant concerns regarding the confidentiality of biometric data. This study presents a groundbreaking approach to address these concerns by integrating homomorphic encryption into retina-based authentication. The combination of homomorphic encryption and retina biometrics within the proposed framework offers a comprehensive solution that ensures both privacy and security with no loss in accuracy. The proposed approach mitigates the risks associated with possible unauthorised access and security breaches by keeping the data encrypted throughout the entire procedure. Furthermore, it preserves the individual’s privacy by preventing the exposure of sensitive biometric information. We evaluated the proposed system through extensive experiments and simulations, demonstrating its effectiveness in terms of both security and privacy when the system operates in normal (ideal) and abnormal (under attack) conditions. Experimental results indicate that the combined approach offers robust resistance to various attacks, including replay attacks and data exposure, providing a robust and privacy-centric authentication solution.
... The debate surrounding the development of technologies utilizing biometric data is evident in responses to content addressing biometric data and security systems in videos. Advocates highlight the potential of biometric technologies to bolster security measures through enhanced authentication processes, minimizing the risks associated with traditional methods like passwords or PINs [15]- [17]. Moreover, proponents argue that biometric systems offer unparalleled accuracy and efficiency in identifying individuals, thus facilitating seamless access to restricted areas or sensitive information [18]- [20]. ...
This study investigates sentiment analysis methodologies within the framework of CRISP-DM (Cross-Industry Standard Process for Data Mining), aiming to discern the efficacy of various algorithms in sentiment classification tasks. The research uses a structured approach to evaluate SVM, NBC, DT, and K-NN algorithms with the SMOTE oversampling technique, uncovering distinct performance metrics and limitations. Results indicate SVM achieving 59.88% accuracy, NBC at 59.25%, DT with 52.09%, and K-NN obtaining 54.80%, highlighting the differential precision, recall, and f-measure. Additionally, content analysis identifies pertinent themes such as Biometric security, Cloud storage, and Emotion Analysis, enriching sentiment dynamics comprehension. The toxicity scores of analyzed videos reveal nuanced sentiment nuances, with the first video exhibiting Toxicity: 0.13227 and the second scoring Toxicity: 0.12794. This study underscores the significance of informed algorithm selection and evaluation methodologies within CRISP-DM, fostering optimized sentiment analysis outcomes while acknowledging diverse topical nuances.
... 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. ...
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.
... The most common technologies used to collect palm vein images are near-infrared (NIR) and far-infrared (FIR) radiation. NIR is considered better than FIR because it is more tolerant to environmental changes (temperature or humidity) [5][6][7]. On the other hand, NIR 'faces the problem of pattern corruption because of visible skin features being mistaken for veins' [8]. IR technology is easily acceptable by users because it is contactless but, on the other hand, it allows one to collect only 2D patterns. ...
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.
... 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 ...
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.
... 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]. ...
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.
... The algorithm had good security, but poor discrimination and robustness. Similarly, zero leakage biometric protection [1,25] had good security, but its complexity was high. Moreover, the diversity and security of biological template were not considered in the above algorithms. ...
In order to solve the problem of plaintext data leakage, and to improve the diversity and security of biometric template, this paper proposes a high security BioHashing encrypted speech retrieval algorithm based on feature fusion, and introduces K-means-KNN fusion algorithm to classify. Firstly, the features of speech are extracted through FFT and IFFT. Secondly, the fused features are classified and a single mapping secret key is assigned to each class. The improved Marotto chaos measurement matrix is generated by the secret key, and the BioHashing sequences are generated by iterating the measurement matrix with the feature data. Then, the speech clips are classified and a single mapping secret key is assigned to each class. The SPM(sine map and piece wise linear chaotic map) chaotic sequence is generated by the secret key and the speech clips are encrypted by the sequence. Finally, hash indexes and encrypted speech clips are uploaded to the cloud, the normalized Hamming distance algorithm is used for matching retrieval on the user terminal. Experimental results show that the algorithm not only effectively prevents plaintext data leakage, but also achieves 100% retrieval accuracy for the original speech clips. Moreover, there are 18 classes of biometric templates, which have good security and key revocability.
