Статті в журналах: "Fast biometry"

1

Turczynowska, Magdalena, Katarzyna Koźlik-Nowakowska, Magdalena Gaca-Wysocka, and Andrzej Grzybowski. "Effective Ocular Biometry and Intraocular Lens Power Calculation." European Ophthalmic Review 10, no. 02 (2016): 94. http://dx.doi.org/10.17925/eor.2016.10.02.94.

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Since the introduction of phacoemulsification, cataract surgery has evolved remarkably. The use of premium intraocular lenses (IOLs) (aspheric, toric, multifocal), refractive lens exchange and patients after refractive surgery procedures require extremely precise clinical measurements and IOL calculation formulas to achieve desired postoperative refraction. For many years, ultrasound biometry has been the standard for measurement of ocular parameters. The introduction of optical biometry (fast and non-invasive) has replaced ultrasound methods and is now considered as the clinical standard for ocular biometry. Recently, several modern optical instruments have been commercially launched and there are new methods available, including the empirical, analytical, numerical or combined methods to determine IOL power. The aim of this review is to present current techniques of ocular biometry and IOL power calculation formulas, which will contribute to achieve highly accurate refractive outcomes.

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2

Herbadji, Abderrahmane, Zahid Akhtar, Kamran Siddique, Noubeil Guermat, Lahcene Ziet, Mohamed Cheniti, and Khan Muhammad. "Combining Multiple Biometric Traits Using Asymmetric Aggregation Operators for Improved Person Recognition." Symmetry 12, no. 3 (March 10, 2020): 444. http://dx.doi.org/10.3390/sym12030444.

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Biometrics is a scientific technology to recognize a person using their physical, behavior or chemical attributes. Biometrics is nowadays widely being used in several daily applications ranging from smart device user authentication to border crossing. A system that uses a single source of biometric information (e.g., single fingerprint) to recognize people is known as unimodal or unibiometrics system. Whereas, the system that consolidates data from multiple biometric sources of information (e.g., face and fingerprint) is called multimodal or multibiometrics system. Multibiometrics systems can alleviate the error rates and some inherent weaknesses of unibiometrics systems. Therefore, we present, in this study, a novel score level fusion-based scheme for multibiometric user recognition system. The proposed framework is hinged on Asymmetric Aggregation Operators (Asym-AOs). In particular, Asym-AOs are estimated via the generator functions of triangular norms (t-norms). The extensive set of experiments using seven publicly available benchmark databases, namely, National Institute of Standards and Technology (NIST)-Face, NIST-Multimodal, IIT Delhi Palmprint V1, IIT Delhi Ear, Hong Kong PolyU Contactless Hand Dorsal Images, Mobile Biometry (MOBIO) face, and Visible light mobile Ocular Biometric (VISOB) iPhone Day Light Ocular Mobile databases have been reported to show efficacy of the proposed scheme. The experimental results demonstrate that Asym-AOs based score fusion schemes not only are able to increase authentication rates compared to existing score level fusion methods (e.g., min, max, t-norms, symmetric-sum) but also is computationally fast.

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Taha, Mohammed A., and Hanaa M. Ahmed. "A fuzzy vault development based on iris images." EUREKA: Physics and Engineering, no. 5 (September 13, 2021): 3–12. http://dx.doi.org/10.21303/2461-4262.2021.001997.

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Biometric systems gather information from the person's biometric attributes, used extensively to authorize the individuals. Due to the obvious convenience of using specific individual traits such as face, fingerprints, palm veins, and irises, biometric authentication is becoming more common. In particular, Iris systems are in high demand for high-assurance applications, because they contain a broad feature set and remain stable. Authentication methods based on iris biometrics are now commonly used in a variety of fields. This is due to the fact that iris biometric authentication is both safer and more comfortable than conventional passwords. Template Security is a major concern in biometric systems. The template security mechanism ensures reusable, permanent, and un-linkable models. The Fuzzy Vault strategy is one of the most popular security schemes for Template protection. Fuzzy vault has demonstrated to be an effective protection method but lacks revocability and security attacks. This article introduced an improved fuzzy vault system. The improved fuzzy vault system was introduced, which uses more than one key to protect biometric data. Different keys make the search space more detailed. The additional key was used to encrypt vault data, which stopped the intruder from accessing the information on the person's biometry. The system was tested using CASIA.v1 and IITD.v1 datasets, and findings showed that the system ensures the protection and authentication of the iris templates without compromising performance. The proposed modification gave a 0.0 % False Accepted Rate (FAR) for both the dataset and False Rejected Rate (FRR), 0.14 % for CASIA v1 and 0.12 % for ITTD v1 False Rejected rate

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4

Behrensen, Maren. "Identity as convention: biometric passports and the promise of security." Journal of Information, Communication and Ethics in Society 12, no. 1 (March 4, 2014): 44–59. http://dx.doi.org/10.1108/jices-08-2013-0029.

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Purpose – The paper is a conceptual investigation of the metaphysics of personal identity and the ethics of biometric passports. The paper aims to discuss these issues. Design/methodology/approach – Philosophical argument, discussing both the metaphysical and the social ethics/computer ethics literature on personal identity and biometry. Findings – The author argues for three central claims in this paper: passport are not simply representations of personal identity, they help constitute personal identity. Personal identity is not a metaphysical fact, but a set of practices, among them identity management practices (e.g. population registries) employed by governments. The use of biometry as part of these identity management practices is not an ethical problem as such, nor is it something fundamentally new and different compared to older ways of establishing personal identity. It is worrisome, however, since in the current political climate, it is systematically used to deny persons access to specific territories, rights, and benefits. Originality/value – The paper ties together strands of philosophical inquiry that do not usually converse with one another, namely the metaphysics of personal identity, and the topic of identity in social philosophy and computer ethics.

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5

Rana, Humayan Kabir, Md Shafiul Azam, Mst Rashida Akhtar, Julian M. W. Quinn, and Mohammad Ali Moni. "A fast iris recognition system through optimum feature extraction." PeerJ Computer Science 5 (April 8, 2019): e184. http://dx.doi.org/10.7717/peerj-cs.184.

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With an increasing demand for stringent security systems, automated identification of individuals based on biometric methods has been a major focus of research and development over the last decade. Biometric recognition analyses unique physiological traits or behavioral characteristics, such as an iris, face, retina, voice, fingerprint, hand geometry, keystrokes or gait. The iris has a complex and unique structure that remains stable over a person’s lifetime, features that have led to its increasing interest in its use for biometric recognition. In this study, we proposed a technique incorporating Principal Component Analysis (PCA) based on Discrete Wavelet Transformation (DWT) for the extraction of the optimum features of an iris and reducing the runtime needed for iris template classification. The idea of using DWT behind PCA is to reduce the resolution of the iris template. DWT converts an iris image into four frequency sub-bands. One frequency sub-band instead of four has been used for further feature extraction by using PCA. Our experimental evaluation demonstrates the efficient performance of the proposed technique.

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6

Dey, Somnath, and Debasis Samanta. "Fast and accurate personal identification based on iris biometric." International Journal of Biometrics 2, no. 3 (2010): 250. http://dx.doi.org/10.1504/ijbm.2010.033389.

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7

Van Oort, Madison. "The Emotional Labor of Surveillance: Digital Control in Fast Fashion Retail." Critical Sociology 45, no. 7-8 (July 13, 2018): 1167–79. http://dx.doi.org/10.1177/0896920518778087.

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Rooted in critical labor studies and feminist surveillance studies, this article explores how big data and biometric surveillance impact fast fashion’s predominantly feminized and racialized workforce. Through ethnography and interviews, I find that automated flexible scheduling, a now widely documented phenomenon, not only disciplines just-in-time staff but also encourages additional forms of digital control—including biometric scanners and point-of-sale metrics. While the technologies described exhibit regular limitations, such as failure and vulnerability to sabotage, they nevertheless have the cumulative effect of exacerbating worker insecurity and reinforcing inequality. I argue that alongside the decline of interactive emotional service work in low-wage retail, emerges another kind of affective labor—that of working amid often invisible yet pervasive digital monitoring. I call this work “the emotional labor of surveillance.”

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8

Abiyev, Rahib Hidayat, and Koray Altunkaya. "Neural network based biometric personal identification with fast iris segmentation." International Journal of Control, Automation and Systems 7, no. 1 (February 2009): 17–23. http://dx.doi.org/10.1007/s12555-009-0103-1.

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9

Dobriban, E. "Fast closed testing for exchangeable local tests." Biometrika 107, no. 3 (February 10, 2020): 761–68. http://dx.doi.org/10.1093/biomet/asz082.

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Summary Multiple hypothesis testing problems arise naturally in science. This note introduces a new fast closed testing method for multiple testing which controls the familywise error rate. Controlling the familywise error rate is state-of-the-art in many important application areas and is preferred over false discovery rate control for many reasons, including that it leads to stronger reproducibility. The closure principle rejects an individual hypothesis if all global nulls of subsets containing it are rejected using some test statistics. It takes exponential time in the worst case. When the tests are symmetric and monotone, the proposed method is an exact algorithm for computing the closure, is quadratic in the number of tests, and is linear in the number of discoveries. Our framework generalizes most examples of closed testing, such as Holm’s method and the Bonferroni method. As a special case of the method, we propose the Simes and higher criticism fusion test, which is powerful both for detecting a few strong signals and for detecting many moderate signals.

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10

KOHN, ROBERT, and CRAIG F. ANSLEY. "Fast filtering for seasonal moving average models." Biometrika 73, no. 2 (1986): 522–24. http://dx.doi.org/10.1093/biomet/73.2.522.

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11

Kang, Sun-Kyoung. "Fast Identity Online-Based Facial Authentication System Development in Mobile." Journal of Computational and Theoretical Nanoscience 18, no. 5 (May 1, 2021): 1582–85. http://dx.doi.org/10.1166/jctn.2021.9599.

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Recently, research on methods to improve upon the security vulnerability of password based authentication is being actively conducted. Research on how to use real-time biometric recognition is also actively underway. The system development of Public Key Infrastructure (PKI) key pairs and uses a method that safely stores the produced keys in secure zones, and encryption key data is composed so that access can only be made in Fast Identity Online (FIDO) Authenticator zones. Face certification data extracted from the face recognition engine is created, data can be accessed and saved through encryption. With the Fast Identity Online (FIDO) Authenticator, a method was developed that compares and face certification data. The system in this thesis developed a Fast Identity Online (FIDO) based face certification system that uses biometric authentication to supplement the weaknesses of password based systems which were used for user certification in the past because they cost little and are convenient. System development in this thesis was conducted by applying a Fast Identity Online (FIDO) based certification system to an Active Shape Model (ASM) style face recognition algorithm. After taking a photo of the face with the user’s cellular phone and saving it, certification is carried out through comparisons made of the photo and real-time input images. Once certification is made using Fast Identity Online (FIDO) protocols, tests of face detection speed and matching speed are conducted to measure accuracy and speed. A total of 30 tests were conducted and test results showed that detection speed was an average of 30.35 f/s and matching speed was 14.16 ms. In this paper, biometric authentication security and convenience are provided by using security functions provided by user devices and supplementing them with a server operation method.

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12

DiCICCIO, THOMAS J., MICHAEL A. MARTIN, and G. ALASTAIR YOUNG. "Fast and accurate approximate double bootstrap confidence intervals." Biometrika 79, no. 2 (1992): 285–95. http://dx.doi.org/10.1093/biomet/79.2.285.

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13

Sluganovic, Ivo, Marc Roeschlin, Kasper B. Rasmussen, and Ivan Martinovic. "Analysis of Reflexive Eye Movements for Fast Replay-Resistant Biometric Authentication." ACM Transactions on Privacy and Security 22, no. 1 (January 23, 2019): 1–30. http://dx.doi.org/10.1145/3281745.

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14

Roy, Nilanjana Dutta, and Arindam Biswas. "Fast and robust retinal biometric key generation using deep neural nets." Multimedia Tools and Applications 79, no. 9-10 (December 18, 2019): 6823–43. http://dx.doi.org/10.1007/s11042-019-08507-y.

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15

Srivastva, Ranjeet, Ashutosh Singh, and Yogendra Narain Singh. "PlexNet: A fast and robust ECG biometric system for human recognition." Information Sciences 558 (May 2021): 208–28. http://dx.doi.org/10.1016/j.ins.2021.01.001.

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16

Coelho, João, Beatriz Fidalgo, Manuel M. Crisóstomo, Raúl Salas-González, A. Paulo Coimbra, and Mateus Mendes. "Non-Destructive Fast Estimation of Tree Stem Height and Volume Using Image Processing." Symmetry 13, no. 3 (February 25, 2021): 374. http://dx.doi.org/10.3390/sym13030374.

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Measuring biometric tree characteristics to estimate the volume of wood in a forest area is a time consuming task. It is usually performed by a team of two or more people, who measure the diameter and height of several trees in sampling plots. The results are then extrapolated for the forest stand. The present paper describes a method which facilitates estimating tree biometric parameters using computational techniques. A camera takes two pictures of each sample tree, with an especially designed target placed close to the tree, to facilitate image processing and camera calibration steps. Taking advantage of the trees’ natural shape and assuming a symmetric stem, the diameter and height of the tree stems are estimated from the images and the volumes of the tree stems are calculated. Experimental trials show promising results, exhibiting errors similar to the traditional methods used currently, in the range of 10%, showing that the method is suitable for forest inventory.

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17

QUINN, B. G., and J. M. FERNANDES. "A fast efficient technique for the estimation of frequency." Biometrika 78, no. 3 (1991): 489–97. http://dx.doi.org/10.1093/biomet/78.3.489.

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Gorbunova, N. Yu, A. A. Voskresenskaya, R. A. Yakovlev, and N. A. Pozdeeva. "Analysis of Ocular Biometric Parameters in Patients with Cystoid Macular Edema." EYE GLAZ 23, no. 4 (December 12, 2021): 7–11. http://dx.doi.org/10.33791/2222-4408-2021-4-7-11.

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Relevance. Cataract surgeries are among the most frequently performed ophthalmic surgeries in the world. Despite the fact that they become less traumatic every year, such interventions are still accompanied by post-surgery complications, one of which is cystic macular edema (CME) or Irwin–Gass syndrome. Purpose. To analyze ocular biometric parameters in patients with CME. Material and Methods. The study included 40 patients (40 eyes) with post-surgery CME. All patients underwent ultrasound biometry, axial length measurement, crystalline lens thickness measurement with Bio&Pachy Meter AL-4000 (Tomey, Japan) and optical coherence tomography (OCT) with Cirrus HD-OCT 5000 (Carl Zeiss, Germany) to assess central foveal thickness. Depending on the axial length, all eyes were divided into “long” and “short” relative to the average axial length of 23.3 mm. The data was analyzed with STATISTICA 10 software (StatSoft Inc., USA). Results. The incidence of CME after uncomplicated cataract surgery in Cheboksary branch of the S. Fyodorov Eye Microsurgery Federal State Institution amounted to 0.002%. Axial length among patients with CME ranged from 20.53 mm to 25.4 mm; the average value amounted to 22.67 ± 1.05 mm. The majority of eyes were “short” – 31 eyes (77.5%), whereas 9 eyes (22.5%) were “long”. “Short” eyes exhibited a greater crystalline lens thickness (4.81 ± 0.53 mm) compared to “long” eyes (4.42 ± 0.42 mm) (рM-U = 0.014). Conclusion. The development of CME after uncomplicated cataract surgery is more often observed in eyes with axial length smaller than 23.3 mm.

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19

Guan, Y. "Fast block variance estimation procedures for inhomogeneous spatial point processes." Biometrika 96, no. 1 (January 24, 2009): 213–20. http://dx.doi.org/10.1093/biomet/asn072.

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20

Lei, J. "Fast exact conformalization of the lasso using piecewise linear homotopy." Biometrika 106, no. 4 (September 30, 2019): 749–64. http://dx.doi.org/10.1093/biomet/asz046.

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Summary Conformal prediction is a general method that converts almost any point predictor to a prediction set. The resulting set retains the good statistical properties of the original estimator under standard assumptions, and guarantees valid average coverage even when the model is mis-specified. A main challenge in applying conformal prediction in modern applications is efficient computation, as it generally requires an exhaustive search over the entire output space. In this paper we develop an exact and computationally efficient conformalization of the lasso and elastic net. The method makes use of a novel piecewise linear homotopy of the lasso solution under perturbation of a single input sample point. As a by-product, we provide a simpler and better-justified online lasso algorithm, which may be of independent interest. Our derivation also reveals an interesting accuracy-stability trade-off in conformal inference, which is analogous to the bias-variance trade-off in traditional parameter estimation. The practical performance of the new algorithm is demonstrated in both synthetic and real data examples.

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EDWARDS, DAVID, and HAVRÁNEK TOMÁˇ. "A fast procedure for model search in multidimensional contingency tables." Biometrika 72, no. 2 (1985): 339–51. http://dx.doi.org/10.1093/biomet/72.2.339.

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JONG, P. D., and S. CHU-CHUN-LIN. "Fast likelihood evaluation and prediction for nonstationary state space models." Biometrika 81, no. 1 (March 1, 1994): 133–42. http://dx.doi.org/10.1093/biomet/81.1.133.

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23

Basha. "Efficient Multimodal Biometric Authentication Using Fast Fingerprint Verification and Enhanced Iris Features." Journal of Computer Science 7, no. 5 (May 1, 2011): 698–706. http://dx.doi.org/10.3844/jcssp.2011.698.706.

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24

Giot, Romain, Mohamad El-Abed, and Christophe Rosenberger. "Fast computation of the performance evaluation of biometric systems: Application to multibiometrics." Future Generation Computer Systems 29, no. 3 (March 2013): 788–99. http://dx.doi.org/10.1016/j.future.2012.02.003.

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25

Bassit, Amina, Florian Hahn, Joep Peeters, Tom Kevenaar, Raymond Veldhuis, and Andreas Peter. "Fast and Accurate Likelihood Ratio-Based Biometric Verification Secure Against Malicious Adversaries." IEEE Transactions on Information Forensics and Security 16 (2021): 5045–60. http://dx.doi.org/10.1109/tifs.2021.3122823.

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T., Vijayakumar. "Synthesis of Palm Print in Feature Fusion Techniques for Multimodal Biometric Recognition System Online Signature." Journal of Innovative Image Processing 3, no. 2 (July 1, 2021): 131–43. http://dx.doi.org/10.36548/jiip.2021.2.005.

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Biometric identification technology is widely utilized in our everyday lives as a result of the rising need for information security and safety laws throughout the world. In this aspect, multimodal biometric recognition (MBR) has gained significant research attention due to its ability to overcome several important constraints in unimodal biometric systems. Henceforth, this research article utilizes multiple features such as an iris, face, finger vein, and palm print for obtaining the highest accuracy to identify the exact person. The utilization of multiple features from the person improves the accuracy of biometric system. In many developed countries, palm print features are employed to provide the most accurate identification of an actual individual as fast as possible. The proposed system can be very suitable for the person who dislikes answering many questions for security authentication. Moreover, the proposed system can also be used to minimize the extra questionnaire by achieving a highest accuracy than other existing multimodal biometric systems. Finally, the results are computed and tabulated in this research article.

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Joseph, Annie Anak, Alex Ng Ho Lian, Kuryati Kipli, Kho Lee Chin, Dayang Azra Awang Mat, Charlie Sia Chin Voon, David Chua Sing Ngie, and Ngu Sze Song. "Person Verification Based on Multimodal Biometric Recognition." Pertanika Journal of Science and Technology 30, no. 1 (November 24, 2021): 161–83. http://dx.doi.org/10.47836/pjst.30.1.09.

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Nowadays, person recognition has received significant attention due to broad applications in the security system. However, most person recognition systems are implemented based on unimodal biometrics such as face recognition or voice recognition. Biometric systems that adopted unimodal have limitations, mainly when the data contains outliers and corrupted datasets. Multimodal biometric systems grab researchers’ consideration due to their superiority, such as better security than the unimodal biometric system and outstanding recognition efficiency. Therefore, the multimodal biometric system based on face and fingerprint recognition is developed in this paper. First, the multimodal biometric person recognition system is developed based on Convolutional Neural Network (CNN) and ORB (Oriented FAST and Rotated BRIEF) algorithm. Next, two features are fused by using match score level fusion based on Weighted Sum-Rule. The verification process is matched if the fusion score is greater than the pre-set threshold. The algorithm is extensively evaluated on UCI Machine Learning Repository Database datasets, including one real dataset with state-of-the-art approaches. The proposed method achieves a promising result in the person recognition system.

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Thanki, Rohit, Surekha Borra, and Ashish Kothari. "Fragile Watermarking Framework for Tamper Detection of Color Biometric Images." International Journal of Digital Crime and Forensics 13, no. 2 (March 2021): 35–56. http://dx.doi.org/10.4018/ijdcf.2021030103.

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Application of fragile watermarking on biometric images stored at a server or cloud ensures proper authentication and tamper detection when access to the servers was shared. In this paper, a hybrid domain fragile watermarking technique for authenticity of color biometric images, using hybridization of various transforms such as discrete cosine transform (DCT), fast discrete curvelet transform (FDCuT), and singular value decomposition (SVD) is proposed. The hybrid transform coefficients are modified according to the scrambled color watermark to obtain watermarked color biometric image. The security of this technique is strengthened with the usage of Arnold scrambling, and by using multiple secret keys. The proposed technique is analyzed on FEI Brazilian face database. The experimental results show that this technique performs better than the existing fragile watermarking techniques.

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Bhattacharya, Anirban, Antik Chakraborty, and Bani K. Mallick. "Fast sampling with Gaussian scale mixture priors in high-dimensional regression." Biometrika 103, no. 4 (October 27, 2016): 985–91. http://dx.doi.org/10.1093/biomet/asw042.

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N. F., Antonie. "Environment friendly population records system using biometric data and anonymous signatures." Scientific Bulletin of Naval Academy XXII, no. 1 (July 15, 2019): 112–21. http://dx.doi.org/10.21279/1454-864x-19-i1-015.

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The fast evolution of technology allowed our society to search for ways to increase efficiency and productivity. In some domains this increase in efficiency also lead to less waste, which in turn may lead to better environment protection. Such a domain is that of population records. One way to properly identify an individual is to keep a record of his biometric data. Unfortunately this method of identification is raising a lot of concerns regarding privacy and the protection of private data. This paper proposes a method of protecting biometric data by securing it with anonymous signatures. This will allow the use of that biometric data for identification purposes only and will not link it to individuals without their personal identification card (e.g. passport, ID card, etc.). It is the authors’ belief that this method will increase the number of people to opt for biometric documents which will reduce bureaucracy and implicitly reduce the use of consumable materials thus better protecting the environment.

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Chai, Tong-Yuen, Bok-Min Goi, Yong-Haur Tay, and and Zhe Jin. "A New Design for Alignment-Free Chaffed Cancelable Iris Key Binding Scheme." Symmetry 11, no. 2 (February 1, 2019): 164. http://dx.doi.org/10.3390/sym11020164.

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Iris has been found to be unique and consistent over time despite its random nature. Unprotected biometric (iris) template raises concerns in security and privacy, as numerous large-scale iris recognition projects have been deployed worldwide—for instance, susceptibility to attacks, cumbersome renewability, and cross-matching. Template protection schemes from biometric cryptosystems and cancelable biometrics are expected to restore the confidence in biometrics regarding data privacy, given the great advancement in recent years. However, a majority of the biometric template protection schemes have uncertainties in guaranteeing criteria such as unlinkability, irreversibility, and revocability, while maintaining significant performance. Fuzzy commitment, a theoretically secure biometric key binding scheme, is vulnerable due to the inherent dependency of the biometric features and its reliance on error correction code (ECC). In this paper, an alignment-free and cancelable iris key binding scheme without ECC is proposed. The proposed system protects the binary biometric data, i.e., IrisCodes, from security and privacy attacks through a strong and size varying non-invertible cancelable transform. The proposed scheme provides flexibility in system storage and authentication speed via controllable hashed code length. We also proposed a fast key regeneration without either re-enrollment or constant storage of seeds. The experimental results and security analysis show the validity of the proposed scheme.

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32

Quinn, B. "A fast efficient technique for the estimation of frequency: interpretation and generalisation." Biometrika 86, no. 1 (March 1, 1999): 213–20. http://dx.doi.org/10.1093/biomet/86.1.213.

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BUCKLEY, M. J. "Fast computation of a discretized thin-plate smoothing spline for image data." Biometrika 81, no. 2 (1994): 247–58. http://dx.doi.org/10.1093/biomet/81.2.247.

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Ivanov, Alexander, and Alexeiy Sulavko. "Draft of the Third National Standard of Russia for Fast Automatic Learning of Large Correlation Neural Networks on Small Training Samples of Biometric Data." Voprosy kiberbezopasnosti, no. 3(43) (2021): 84–93. http://dx.doi.org/10.21681/2311-3456-2021-3-84-93.

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The aim of the study is to show that a biometrics-to-access code converter based on large networks of correlation neurons makes it possible to obtain an even longer key at the output while ensuring the protection of biometric data from compromise. The research method is the use of large «wide» neural networks with automatic learning for the implementation of the biometric authentication procedure, ensuring the protection of biometric personal data from compromise. Results of the study - the first national standard GOST R 52633.5 for the automatic training of neuron networks was focused only on a physically secure, trusted computing environment. The protection of the parameters of the trained neural network converters biometrics-code using cryptographic methods led to the need to use short keys and passwords for biometric-cryptographic authentication. It is proposed to build special correlation neurons in the meta-space of Bayes-Minkowski features of a higher dimension. An experiment was carried out to verify the patterns of kkeystroke dynamics using a biometrics-to-code converter based on the data set of the AIConstructor project. In the meta-space of features, the probability of a verification error turned out to be less (EER = 0.0823) than in the original space of features (EER = 0.0864), while in the protected execution mode of the biometrics-to-code converter, the key length can be increased by more than 19 times. Experiments have shown that the transition to the mat space of BayesMinkowski features does not lead to the manifestation of the “curse of dimension” problem if some of the original features have a noticeable or strong mutual correlation. The problem of ensuring the confidentiality of the parameters of trained neural network containers, from which the neural network converter biometrics-code is formed, is relevant not only for biometric authentication tasks. It seems possible to develop a standard for protecting artificial intelligence based on automatically trained networks of Bayesian-Minkowski correlation neurons.

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35

Sharma, Rahul, Nidhi Mishra, and Sanjeev Kumar. "Evaluation of Robustness, Accuracy and Speed of SPIRAL for Fast Fingerprint Biometric System." International Journal of Computer Applications 79, no. 16 (October 18, 2013): 21–26. http://dx.doi.org/10.5120/13945-1911.

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36

Kennedy, M. "Predicting the output from a complex computer code when fast approximations are available." Biometrika 87, no. 1 (March 1, 2000): 1–13. http://dx.doi.org/10.1093/biomet/87.1.1.

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37

Parwanto, Mauritius Lambertus Edy. "Rare defect at superior helix as morphological variation of right auricle." International Journal of Research in Medical Sciences 6, no. 5 (April 25, 2018): 1800. http://dx.doi.org/10.18203/2320-6012.ijrms20181780.

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Auricle is the part of external ear. Morphological appearance and biometric of auricle are influenced by genetic and environmental factors. Base on the fact that morphological appearance and biometric of auricle vary in different human ethnic races. Normal of auricle have complete component with normal of dimension and appearance. Population studies show the different of morphological and biometric of auricle. Generally, the right and left auricles in the individual is symmetrical in both size and appearance. We reported about defect at superior helix of right auricle. In this case it shows that right and left auricles have complete components. The biometric comparison of right and left auricles showed equal or not significant different. Defect of right auricle at superior helix were indentation as morphological variation.

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Iswanto, Bambang, Rommy Suprapto, Imron Imron, Joni Haaryadi, Pudji Suwargono, Maya Febriana Pangestika, and Ilmalizanri Ilmalizanri. "KERAGAAN ZOOTEKNIS DAN BIOMETRIK-MORFOLOGIS IKAN LELE MUTIARA, Clarias gariepinus ALBINO." Jurnal Riset Akuakultur 16, no. 3 (January 31, 2022): 135. http://dx.doi.org/10.15578/jra.16.3.2021.135-144.

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Pemuliaan ikan lele Afrika, Clarias gariepinus melalui seleksi individu selama tiga generasi telah menghasilkan strain baru ikan lele tumbuh cepat yang diberi nama Mutiara. Pemijahan induk ikan lele Mutiara dapat menghasilkan benih albino. Keragaan zooteknis dan karakteristik fenotipe-morfologis ikan lele Mutiara albino perlu dieksplorasi untuk mengevaluasi potensi pengembangannya. Penelitian ini bertujuan mendapatkan informasi keragaan pertumbuhan, sintasan, hubungan panjang-bobot, faktor kondisi, dan karakteristik biometrik ikan lele Mutiara albino dibandingkan yang berwarna normal. Pengamatan keragaan pertumbuhan dilakukan selama 20 hari tahap pemeliharaan larva, 30 hari tahap pendederan dan 45 hari tahap pembesaran. Analisis hubungan panjang-bobot dan faktor kondisi, serta karakterisasi biometrik dilakukan pada akhir tahap pembesaran. Hasil penelitian ini menunjukkan bahwa keragaan pertumbuhan ikan lele Mutiara albino berdasarkan parameter bobot selama tahap pemeliharaan larva, pendederan, dan pembesaran tidak berbeda dari yang berwarna normal (P>0,05); sedangkan keragaan pertumbuhan berdasarkan parameter panjang totalnya lebih rendah (P<0,05). Sintasan ikan lele Mutiara albino selama tahap pemeliharaan larva, pendederan, dan pembesaran tidak berbeda (P>0,05) dari yang berwarna normal. Hubungan panjang-bobot ikan lele Mutiara albino bersifat alometrik positif (W = 0,0021L3,45), sama dengan yang berwarna normal (W = 0,0044L3,16). Ikan lele Mutiara albino memiliki tubuh yang lebih gemuk (faktor kondisi sebesar 0,88 ± 0,08) dibandingkan yang berwarna normal (faktor kondisi sebesar 0,73 ± 0,05). Secara biometrik, ikan lele Mutiara albino memiliki proporsi kepala yang lebih besar dan jumlah jari-jari sirip punggung dan sirip dubur yang lebih sedikit dibandingkan yang berwarna normal. Secara umum, keragaan aspek zooteknis ikan lele Mutiara albino relatif sama dengan yang berwarna normal, sehingga potensial sebagai komoditas budidaya.A breeding program of the African catfish, Clarias gariepinus via three generations of individual selection resulted in a new fast-growing strain, namely Mutiara. Breeding of the Mutiara African catfish might result in albino individuals. Zootechnical and morphological-phenotypic performances of the albino should be evaluated to determine its potential as an aquaculture strain. The present study aimed to obtain information on the growth performance, survival, length-weight relationship, condition factors, and biometric characteristics of the albino compared to those of the normal ones. The growth performance was observed during 20 days of larval rearing, 30 days of nursery, and 45 days of grow-out phases. While, length-weight relationship, condition factors, and biometric characteristics were measured at the end of the grow-out phase. The present study revealed that the growth performance of the albino based on body weight during larval rearing, nursery, and grow-out phases was not different (P>0.05), whereas its growth performance based on total length was inferior (P<0.05) to that of the normal ones. The survival rate of the albino during larval rearing, nursery, and grow-out phases was not different (P>0.05) to that of the normal ones. Length-weight relationship of the albino was positive allometric (W = 0.0021L3.45), similar to that of the normal ones (W = 0.0044L3.16). The albino was more rotund (condition factor of 0.88 ± 0.08) compared to the normal ones (condition factor of 0.73 ± 0.05). Biometrically, the albino has a bigger head portion and fewer dorsal and anal fin rays than the normal ones. In general, the zootechnical aspect of albino Mutiara African catfish is relatively similar to that of the normal ones meaning that it has the potential to be considered as an aquaculture strain candidate.

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39

Et. al., Meena Tiwari. "Enhancing the Accuracy of Multimodal Biometric Systems." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (April 11, 2021): 5142–49. http://dx.doi.org/10.17762/turcomat.v12i3.2063.

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: Biometric acknowledgment frameworks have progressed altogether in the most recent decade and their utilization in explicit applications will increment sooner rather than later. The capacity to direct important correlations and evaluations will be urgent to fruitful organization and expanding biometric selection. Indeed, even the best methodology and unimodal biometric frameworks couldn't completely address the issue of exactness and execution as far as their bogus acknowledge rate (FAR) and bogus oddball rate (FRR). In spite of the fact that multimodal biometric frameworks had the option to moderate a portion of the restrictions experienced in unimodal biometric frameworks, like non-all inclusiveness, uniqueness, non-adequacy, loud sensor information, parody assaults, and execution, the issue of low exactness actually continues. In this paper, we survey research papers zeroed in on the precision improvement in data combination of face and finger impression biometric acknowledgment frameworks, decide the primary highlights of the chose techniques, and afterward call attention to their benefits and inadequacies. We propose a novel methodology in relieving the issue of exactness and execution of data combination of multimodal biometric frameworks. This methodology utilizes multilayer perceptron neural organizations in preparing and testing of the organization while additionally proposing the utilization of the most well-known utilized unique mark in biometric field.

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40

Medjahed, Chahreddine, Abdellatif Rahmoun, Christophe Charrier, and Freha Mezzoudj. "A deep learning-based multimodal biometric system using score fusion." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (March 1, 2022): 65. http://dx.doi.org/10.11591/ijai.v11.i1.pp65-80.

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Recent trends in artificial intelligence tools-based biometrics have overwhelming attention to security matters. The hybrid approaches are motivated by the fact that they combine mutual strengths and they overcome their limitations. Such approaches are being applied to the fields of biomedical engineering. A biometric system uses behavioural or physiological characteristics to identify an individual. The fusion of two or more of these biometric unique characteristics contributes to improving the security and overcomes the drawbacks of unimodal biometric-based security systems. This work proposes efficent multimodal biometric systems based on matching score concatenation fusion of face, left and right palm prints. Multimodal biometric identification systems using convolutional neural networks (CNN) and k-nearest neighbors (KNN) are proposed and trained to recognize and identify individuals using multi-modal biometrics scores. Some popular biometrics benchmarks such as FEI face dataset and IITD palm print database are used as raw data to train the biometric systems to design a strong and secure verification/identification system. Experiments are performed on noisy datasets to evaluate the performance of the proposed model in extreme scenarios. Computer simulation results show that the CNN and KNN multi-modal biometric system outperforms most of the most popular up to date biometric verification techniques.

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D S, Dr Dinesh Kumar. "Human Authentication using Face, Voice and Fingerprint Biometrics." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 15, 2021): 853–62. http://dx.doi.org/10.22214/ijraset.2021.36381.

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Multimodal biometric approaches are growing in importance for personal verification and identification, since they provide better recognition results and hence improve security compared to biometrics based on a single modality. In this project, we present a multimodal biometric system that is based on the fusion of face, voice and fingerprint biometrics. For face recognition, we employ Haar Cascade Algorithm, while minutiae extraction is used for fingerprint recognition and we will be having a stored code word for the voice authentication, if any of these two authentication becomes true, the system consider the person as authorized person. Fusion at matching score level is then applied to enhance recognition performance. In particular, we employ the product rule in our investigation. The final identification is then performed using a nearest neighbour classifier which is fast and effective. Experimental results confirm that our approach achieves excellent recognition performance, and that the fusion approach outperforms biometric identification based on single modalities.

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Gore, Dayanand Bharat. "Comparative Study on Feature Extractions for Ear Recognition." International Journal of Applied Evolutionary Computation 10, no. 2 (April 2019): 8–18. http://dx.doi.org/10.4018/ijaec.2019040102.

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Biometrics includes the study of automatic methods for distinguishing human beings based on physical or behavioural traits. The problem of finding good biometric features and recognition methods has been researched extensively in recent years. This research considers the use of ears as a biometric for human recognition. In this article, basic feature extraction techniques are implemented such as Harris Feature, FAST Feature extraction and SURF Feature Extraction. All the images are taken from standard database and each image has different angles because of any criminal investigation, accident, or ATM machine camera taken different types of images. So, using different images feature extraction the research goes through these techniques to give the best result to the user.

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43

KOHN, ROBERT, and CRAIG F. ANSLEY. "A fast algorithm for signal extraction, influence and cross-validation in state space models." Biometrika 76, no. 1 (1989): 65–79. http://dx.doi.org/10.1093/biomet/76.1.65.

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44

Okokpujie, Kennedy, John Abubakar, Samuel John, Etinosa Noma-Osaghae, Charles Ndujiuba, and Imhade Princess Okokpujie. "A secured automated bimodal biometric electronic voting system." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 1 (March 1, 2021): 1. http://dx.doi.org/10.11591/ijai.v10.i1.pp1-8.

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Insecurity, rigging and violence continue to mar electoral processes in developing nations. It has been difficult to enforce security and transparency in the voting process. This paper proposes a secure and automated bimodal voting system. The system uses three security layers, namely, a unique ID code, a token passcode that expires every five minutes and biometrics (iris and fingerprint). A scanner captures the fingerprint and iris of eligible voters. The fingerprint and iris images stored along with the corresponding particulars in a database. The software implemented is a .net managed code in C#. The result of this system shows the system is transparent, fast and fraud-free. The proposed method had a failure to enroll (FTE) and a failure to capture (FTC) of zero.

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45

Ganeshan, Balaji, Dhananjay Theckedath, Rupert Young, and Chris Chatwin. "Biometric iris recognition system using a fast and robust iris localization and alignment procedure." Optics and Lasers in Engineering 44, no. 1 (January 2006): 1–24. http://dx.doi.org/10.1016/j.optlaseng.2005.03.010.

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46

Sufi, Fahim, Ibrahim Khalil, and Abdun Mahmood. "Compressed ECG Biometric: A Fast, Secured and Efficient Method for Identification of CVD Patient." Journal of Medical Systems 35, no. 6 (January 6, 2010): 1349–58. http://dx.doi.org/10.1007/s10916-009-9412-4.

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47

Khalil-Hani, Mohamed, Muhammad N. Marsono, and Rabia Bakhteri. "Biometric encryption based on a fuzzy vault scheme with a fast chaff generation algorithm." Future Generation Computer Systems 29, no. 3 (March 2013): 800–810. http://dx.doi.org/10.1016/j.future.2012.02.002.

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48

Kuznetsov, A. A. "Legal Basis of Biometric Methods of Identity Authentication." Economics. Law. Innovaion, no. 1 (March 30, 2021): 85–90. http://dx.doi.org/10.17586/2713-1874-2021-1-85-90.

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The paper substantiates the need to form the legal foundations of biometric authentication methods. The development of modern society is connected with the protection of information and information security. Biometric authentication methods are of interest as an innovative technology, the use of which should have an appropriate legal basis. The implementation of the necessary software must be regulated by separate provisions of copyright law. The use of biometric parameters of a person must also be subject to legal acts. The separation of the two concepts of authentication and identification in the legal aspect is justified. This is due to the fact that the possibility of access to both personal data of the individual and their financial assets is affected, since the main sphere of use of biometric parameters is the receipt of public and banking services. The regulatory legal acts that determine the possibility of using biometric authentication methods are considered. The paper draws practical conclusions about the need to distinguish an independent legal category of biometric personal data in the Russian legislation. To fix that the information about the subject of personal data will be attributed to biometric identification parameters if it is used for the purpose of establishing identity.

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Jee, Soo-Chan, Ye Lim Rhie, Minjee Kim, Yong Min Kim, Sung Hee Ahn, and Myung Hwan Yun. "Use of Hand Biometric Information in Gender Identification." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 851–54. http://dx.doi.org/10.1177/1541931213601194.

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These days, mobile devices are expected to act as biometric readers due to their increasing number of sensors. However, few studies have suggested a method to identify the user’s demographic profile by collecting biometric information through smart devices, whereas demographic characteristics are an important factor that determines the overall preferences of the interface and content. Therefore, this paper suggests a method to identify the user’s gender based on the biometric information of users. Since the hand is one of the most frequently used body parts in touch interfaces, four hand dimensions and the EMG activities of four hand muscles were measured. The hand length, hand breadth, hand thickness, and hand circumference of 321 Koreans were collected as hand dimensions, and the EMG activities of 27 participants when using mock-ups of mobile phones were observed. As a result of discriminant analysis, hand dimensions could predict males and females with over 75% accuracy, while %MVC showed relatively lower accuracy. The results revealed that simple hand dimensions are a more efficient method to recognize the gender of users. In a further study, other biometric data could be utilized in sensing various types of demographic information considering that identification technologies are growing fast.

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Farid, Farnaz, Mahmoud Elkhodr, Fariza Sabrina, Farhad Ahamed, and Ergun Gide. "A Smart Biometric Identity Management Framework for Personalised IoT and Cloud Computing-Based Healthcare Services." Sensors 21, no. 2 (January 14, 2021): 552. http://dx.doi.org/10.3390/s21020552.

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This paper proposes a novel identity management framework for Internet of Things (IoT) and cloud computing-based personalized healthcare systems. The proposed framework uses multimodal encrypted biometric traits to perform authentication. It employs a combination of centralized and federated identity access techniques along with biometric based continuous authentication. The framework uses a fusion of electrocardiogram (ECG) and photoplethysmogram (PPG) signals when performing authentication. In addition to relying on the unique identification characteristics of the users’ biometric traits, the security of the framework is empowered by the use of Homomorphic Encryption (HE). The use of HE allows patients’ data to stay encrypted when being processed or analyzed in the cloud. Thus, providing not only a fast and reliable authentication mechanism, but also closing the door to many traditional security attacks. The framework’s performance was evaluated and validated using a machine learning (ML) model that tested the framework using a dataset of 25 users in seating positions. Compared to using just ECG or PPG signals, the results of using the proposed fused-based biometric framework showed that it was successful in identifying and authenticating all 25 users with 100% accuracy. Hence, offering some significant improvements to the overall security and privacy of personalized healthcare systems.

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