The Image Processing Algorithms  for Biometric Identification by Fingerprints

Mazakov, Talgat; Jomartova, Sh. A.; Shormanov, T. S.; Ziyatbekova, G. Z.; Amirkhanov, B.; Kisała, Piotr

doi:10.32014/2020.2518-170x.2

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…Figure 5 Fingerprint Recognition using ORB. Adapted from [41] Figure 6 Implementation of MTCNN. Adapted from [42] As shown in Figure 8, biometric samples were captured and sent to the AS.…”

Section: Biometric Authenticationmentioning

confidence: 99%

Medical Systems Data Security and Biometric Authentication in Public Cloud Servers

Santos

Ghita

Masala

2024

IEEE Trans. Emerg. Topics Comput.

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Advances in distributed computing and virtualization allowed cloud computing to establish itself as a popular data management and storage option for organizations. However, unclear safeguards, practices, as well as the evolution of legislation around privacy and data protection, contribute to data security being one of the main concerns in adopting this paradigm. Another important aspect hindering the absolute success of cloud computing is the ability to ensure the digital identity of users and protect the virtual environment through logical access controls while avoiding the compromise of its authentication mechanism or storage medium. Therefore, this paper proposes a system that addresses data security wherein unauthorized access to data stored in a public cloud is prevented by applying a fragmentation technique and a NoSQL database. Moreover, a system for managing and authenticating users with multimodal biometrics is also suggested along with a mechanism to ensure the protection of biometric features. When compared with encryption, the proposed fragmentation method indicates better latency performance, highlighting its strong potential use-case in environments with lower latency requirements such as the healthcare IT infrastructure.

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“…Figure 5 Fingerprint Recognition using ORB. Adapted from [41] Figure 6 Implementation of MTCNN. Adapted from [42] As shown in Figure 8, biometric samples were captured and sent to the AS.…”

Section: Biometric Authenticationmentioning

confidence: 99%

Medical Systems Data Security and Biometric Authentication in Public Cloud Servers

Santos

Ghita

Masala

2024

IEEE Trans. Emerg. Topics Comput.

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“…The long service life and reduction in the last 20 years of funding for operating expenses, current and capital repairs, as well as the influence of climatic and seismic factors gradually lead to moral and physical deterioration of the entire complex of hydraulic structures. There are also objects located close to hazardous industries [10][11][12].…”

Section: Issn 2224-5278mentioning

confidence: 99%

Mathematical Modeling Forecasting of Consequences of Damage Breakthrough

Mazakov¹,

Kisala²,

Jomartova³

et al. 2020

SERIES OF GEOLOGY AND TECHNICAL SCIENCES

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The article is devoted to the development of a mathematical model for preventing a breakthrough of a dam and predict its possible consequences. In this work, the task of developing a single integrated approach to ensuring the safe operation of hydraulic structures, based on the notification of interested bodies in real time, was solved. A mathematical model of the state of the reservoir is developed, on the basis of which a hardware-software complex for operational notification of interested organizations (akimats) and local emergency departments is implemented. A mathematical model of predicting the consequences of a dam break is proposed. An algorithm for calculating the maximum level of the breakout wave has been formulated, taking into account many parameters of the hydraulic structures. The convergence of the developed algorithm in the form of a theorem has been proved. This method has a large practical focus, compared with existing formulas. The Java language implements a hardware-software complex (PAC) for predicting the effects of a dam break, consisting of the following modules: 1) a module for receiving and transmitting current information about the water level, humidity and temperature on the crest of the dam; 2) a module for processing constant and operational information about the threat of dam breakthrough (server); 3) a module for predicting the effects of a dam break. Based on the solution of the model problem, the effectiveness of the developed hardware-software complex is shown. The practical basis for the model task was the events that took place in Kyzylagash village of Almaty region of the Republic of Kazakhstan.

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