A new type of augmented reality markers

Main Article Content

Oleksandr Makoveychuk


The subject matter of the article is the augmented reality markers. The goal is to develop a new type of augmented reality tokens that has the advantages of most existing types of tokens and is free from their disadvantages. The tasks are: analysis of the advantages and disadvantages of existing augmented reality markers, formulation of the basic requirements for a Perspective augmented reality marker, development of the main stages of construction of a new augmented reality marker, practical verification of compliance of a new augmented reality marker with the formulated requirements. The methods used are methods of digital image processing, probability theory, mathematical statics, cryptography and information security, mathematical apparatus of matrix theory. The following results were obtained. The advantages and disadvantages of the main existing types of augmented reality markers are identified. The five requirements that new augmented reality tokens must satisfy are formulated. The technique of constructing a new marker of augmented reality is offered, which satisfies the formulated requirements. The accuracy of marker recognition depending on the correlation between its parameters is theoretically substantiated. Conclusions. The areas of further research are the development of a method for determining the parameters of projective transformation that is necessary to align the image and determine the position of the camera; development of a method of finding the correct offset of the aligned image, which is necessary for the correct decoding of the permuted image.

Article Details

Methods of information systems synthesis
Author Biography

Oleksandr Makoveychuk, Kharkiv National University of Radio Electronics, Kharkiv

Candidate of Technical Sciences, doctoral student of Electronic Computers Department


Augmented reality or AR technology (2019), available at: http://thefuture.news/lessons/ua/ar

Goldman, S. (2019), Global Investment Research, available at:


Adobe Blog (2019), The 10 VR Trends We’ll See in 2018, 2019, available at:


Facebook Research. AR/VR-Facebook Research (2019), available at:


Siltanen, S. (2012), Theory and applications of marker-based augmented reality, Espoo 2012, 198 p.

Lowe, David G. (1999), “Object recognition from local scale-invariant features”, Proceedings of the International Conference on Computer Vision 2, pp. 1150–1157.

Bruckstein, A.M., Holt, R.J. and Netravali, A.N. (2000), “Holographic representation of images”, IEEE Transactions on Im-age Processing, No. 7, pp. 1583–1587.

Bruckstein, A.M., Holt, R.J. and Netravali, A.N. (1997), Holographic image representations: the subsampling method, IEEE Int. Conference on Image Processing, Santa Barbara, California, USA, October, Vol. 1, pp. 177–180.

Bruckstein, A.M., Holt, R.J. and Netravali, A.N. (2000), US 6,091,394: "Technique for Holographic Representation of Imag-es". July 18, 6 p.

Barinova, D.A. (2005), Development and research of digital image processing algorithms represented in pseudo-holographic codes, Computer Optics, No. 27, pp. 149–154.

Voronin, V.V. (2000), “Holographic representation in image processing problems”, Abstracts of the ROAI conference, 5, pp. 237–241.

Mathworks. Select a Web Site (2019), available at: https://www.mathworks.com/help/images/ref/stdfilt.html

Hartley, R. and Zisserman, S. (2003), Multiple View Geometry in Computer Vision, Cambridge University Press New York, NY, USA, 655 p.

Forsyth, A.D. and Pons, J. (2004), Computer Vision. Modern Campaign, Williams Publishing House, Moscow, 928 p.

Reed–Solomon codes for coders (2019), available at:


Makoveychuk, O.M., Ruban, I.V. and Khudov G.V. (2019), “Using Genetic Algorithms for Finding Inverse Pseudo-Random Block Rearrangements”, Control, Navigation and Communication Systems, No. 4 (56), pp. 72¬81.