The method of encryption based on Ateb-functions

Nazarkevych, Mariya; Oliiarnyk, Roman; Nazarkevych, Hanna; Kramarenko, O N V O Ie; Onyshschenko, Igor

doi:10.1109/dsmp.2016.7583523

Cited by 16 publications

(7 citation statements)

References 3 publications

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“…is calculated for various values of m and n [27], which are given in Table 1. The properties for Ateb-sa, which are used to construct the imaginary component of the Gabor filter, are similar.…”

Section: Construction and Properties Of Ateb-functions For Filtrationmentioning

confidence: 99%

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Detection of regularities in the parameters of the atebgabor method for biometric image filtration

Nazarkevych

Riznyk

Samotyy

et al. 2019

EEJET

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Розроблено новий метод фiльтрацiї бiометричних зображень на основi Ateb-Габора. Метод базується на загальновiдомому фiльтрi Габора та дозволяє перебудовувати зображення iз чiткiшими контурами. Тому даний метод має застосування до бiометричних зображень, де створення чiтких контурiв є особливо актуальне. При фiльтрацiї Габором вiдбувається реконструкцiя зображення шляхом множення гармонiйної функцiї на функцiю Гауса. Ateb-функцiї є узагальненням елементарної тригонометрiї, i, вiдповiдно, володiють бiльшою функцiональнiстю. Фiльтрування Ateb-Gabor дозволяє змiнювати iнтенсивнiсть всього зображення, а також iнтенсивнiсть у певних дiапазонах, i таким чином зробити певнi дiлянки зображення контраснiшими. Ateb-функцiї змiнюються вiд двох рацiональних параметрiв, а це, в свою чергу, дає можливiсть гнучкiше керувати фiльтрацiєю. Дослiджено властивостi Ateb-функцiї, а також можливостi змiни амплiтуди функцiї, частоти коливань на фiльтр Ateb-Габора. Показано розвинення фiльтрацiї на основi двовимiрного Ateb-Габору. Цi залежностi проаналiзованi та зробленi вiдповiднi експерименти. Здiйснено визначення спiввiдношень мiж частотою та шириною фiльтра Ateb-Габора, що дозволило виконувати фiльтри для знаходження країв об'єктiв з рiзними частотами та розмiрами. Розроблено вiдповiдне програмне забезпечення для фiльтрацiї за допомогою python без використання стороннiх бiблiотек, зв'язаних з обробкою зображень. Вiдбитки пальцiв вiдфiльтрованi за допомогою розробленого фiльтра Ateb-Габора. Показано ефективнiсть його використання, яке полягає у бiльшiй кiлькостi варiантiв фiльтрацiї опрацьованих зображень. Результати численних експериментiв демонструють успiшне видiлення країв на зображеннi на основi отриманих в роботi параметрiв фiльтра Ateb-ГабораКлючовi слова: фiльтр Габора, Ateb-функцiї, бiометрична система, обробка зображень, вiдхилення гаусiвського ядра UDC 004.056.5: 655.25

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Section: Construction and Properties Of Ateb-functions For Filtrationmentioning

confidence: 99%

“…Below is a snippet of the code that calculates the value of Ateb-functions. Numerous methods for calculating Ateb-ca were used in papers [25][26][27]. In this study, odeint was used from the Python scipy library.…”

Section: Image Processing Using the Ateb-gabor Filtermentioning

confidence: 99%

Detection of regularities in the parameters of the atebgabor method for biometric image filtration

Nazarkevych

Riznyk

Samotyy

et al. 2019

EEJET

Self Cite

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“…An alternative approach to solving data encryption tasks using algebraic transformations is considered in [18][19].…”

Section: Analysis Of Publicationsmentioning

confidence: 99%

Neural-Like Means for Data Streams Encryption and Decryption in Real Time

Tsmots

Tsymbal

Khavalko

et al. 2018

2018 IEEE Second International Conference on Data Stream Mining &Amp; Processing (DSMP)

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The "model of successive geometric transformations" paradigm has been adapted for the implementation of parallel-streaming neural network encryption-decryption of data in real time. A model and structure of a parallel-streaming neural-like element for the mode have been developed. Keywords-intensive data stream; neural networks; geometric transformations model I. INTRODUCTION The latest information technologies are becoming global in the modern world. Their development and development of communications provides ever-widening opportunities for access to information resources and the transfer of large amounts of data for unlimited distances. In the context of the intensive development of the market for information products and services, information has become a full-fledged product that has its own consumer properties and cost characteristics. The widespread introduction of information technology makes a relevant problem for the protection of the transmission of information using cryptographic methods that provide encryption of the ready-to-transmit information. The encrypted information is transmitted by a communication channel to an authorized user, who, after receiving it, performs decryption using a reverse transformation. Cryptographic transformations are carried out using special algorithms. In order to encrypt and decrypt real-time data streams, it is suggested to use neural-like network algorithms, the key in which is the network architecture, weighting factors, and masking codes.

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“…Fig. 2 shows the normal Gabor filter, which is displayed with the parameters of the Ateb-function [9] m and n of the unit level. Ten figures show a change of ω from 0.1 to 1.0.…”

Section: Ateb-gabor Filtrationmentioning

confidence: 99%

Research of Ateb-Gabor Filter in Biometric Protection Systems

Nazarkevych

Buriachok

Lotoshynska³

et al. 2018

2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT)

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Biometric recognition systems require the development of new technologies and need improvement. A new filter of Ateb-Gabor has been investigated. The filter is based on the use of a combination of Gabor filter and periodic Atebfunctions. This combination allows us to provide flexibility for control by choosing two parameters m and n, which is provided by the mathematical apparatus of the Ateb functions. Filtration was performed on the example of biometric images. It has been shown that Ateb-Gabor filtration gives better filtration results than ordinary Gabor filter. Experimental research has been carried out.

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The method of encryption based on Ateb-functions

Cited by 16 publications

References 3 publications

Detection of regularities in the parameters of the atebgabor method for biometric image filtration

Detection of regularities in the parameters of the atebgabor method for biometric image filtration

Neural-Like Means for Data Streams Encryption and Decryption in Real Time

Research of Ateb-Gabor Filter in Biometric Protection Systems

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The method of encryption based on Ateb-functions

Cited by 16 publications

References 3 publications

Detection of regularities in the parameters of the ateb­gabor method for biometric image filtration

Detection of regularities in the parameters of the ateb­gabor method for biometric image filtration

Neural-Like Means for Data Streams Encryption and Decryption in Real Time

Research of Ateb-Gabor Filter in Biometric Protection Systems

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Detection of regularities in the parameters of the atebgabor method for biometric image filtration

Detection of regularities in the parameters of the atebgabor method for biometric image filtration