DEVELOPMENT OF MATHEMATICAL MODELS OF PARALLELHIERARCHICAL TRANSFORMATION FOR EFFICIENT IMAGE PROCESSING

Authors

DOI:

https://doi.org/10.32703/2617-9040-2021-37-15

Keywords:

parallel - hierarchical transformations, image processing, parallel-hierarchical networks.

Abstract

This article considers the problems of modern models and methods of recognition of information and images, the analogy of learning parallel-hierarchical networks with RBF networks. During the analysis, it was determined that image processing using the mask method does not use all the power of multi-core systems. The analysis of parallel-hierarchical transformation and image processing is carried out. The analysis of the mathematical model of parallel-hierarchical transformation for speed increase by means of parallel transformation is carried out. The algorithm was simulated using the C # language, and artificially created images using microwave were used for the test. The simulation was performed for complete PI conversion, the simulation results are shown in the tables. Parallel-hierarchical transformation for image processing has great potential in transport systems, it can be used in tasks where it is necessary to quickly analyze images from the camera, such as the presence of obstacles in the trajectory of traffic and collision avoidance, analysis of asphalt damage on the trajectory and suspension adjustment to level the effect. The results obtained in the modeling process allow us to conclude that the speed of parallel-hierarchical transformation in image processing problems.

References

ЛІТЕРАТУРА

Наконечна С. В. Оброблення зображень плям лазерних пучків із застосуванням паралельно-ієрархічних мереж : автореф. дис. на здобуття наук. ступеня канд. тех. наук : 05.13.23 : захист 26.12.2014 / наук. кер. Л. І. Тимченко. Львів, 2014. 27 с.

Saldaña-Heredia A., Márquez-Aguilar P., Lara A., Molina-Ocampo A. Digital Image Processing Applied to Optical Measurements. London. 2020. P. 29-44. DOI: 10.5772/intechopen.88704

Timchenko L, Pijarski P., Zavadskiy V. Processing laser beam spot images using the parallel-hierarchical network for classification and forecasting their energy center coordinates // Proceedings of SPIE - The International Society for Optical Engineering. 2016. DOI: 10.1117/12.2248878

Степанюк Д. С. Метод прогнозування показників біомедичних зображень з використанням паралельно-ієрархічної мережі // Наукові праці Донецького національного технічного університету. Серія : Інформатика, кібернетика та обчислювальна техніка. 2018. № 1. С. 101-105. DOI: 10.31474/1996-1588-2018-1-26-101-105

Метод класифікації зображень плям лазерних пучків із застосуванням паралельно-ієрархічної мережі із підвищеною точністю / Л. І. Тимченко та ін. // Оптико-електронні інформаційно-енергетичні технології.2014. № 1. С. 5-17.

Метод вимірювання координат енергетичного центру зображень протяжних лазерних трас / Л. І. Тимченко та ін. // Збірник наукових праць Державного університету інфраструктури та технологій. Серія : Транспортні системи і технології. 2017. Вип. 31. С. 202-211.

Modified method of parallel-hierarchical network teaching based on population Coding / Timchenko L. and etc. // Information Technology in Medical Diagnostics, CHAPTER – 3. Netherlands. 2017 P. 49-63

Тимченко Л. І., Наконечна С. В. Оброблення зображень плям лазерних пучків із застосуванням паралельно-ієрархічних мереж // ScienceRise. - 2014. - № 3(2). - С. 40-49. DOI: 10.15587/2313-8416.2014.27537

Development of a method of processing images of laser beam bands with the use of parallel hierarchic networks / Tymchenko L. and etc. // Eastern European Journal of Enterprise Technologies. 2019. №6/9(102). P. 21-27. DOI: 10.15587/1729-4061.2019.188568

Ultrafast laser beam shaping for material processing at imaging plane by geometric phase masks using a spatial light modulator / Kuang Z. and etc. London. 2015. DOI: https://doi.org/10.1016/j.optlaseng.2015.02.004

Dynamic beam shaping with polarization control at the image plane for material processing / Tang Y. and etc. Liverpool. 2018. P. 581 – 584. DOI: https://doi.org/10.1016/j.procir.2018.08.083

Processing laser beam images using parallel-hierarchical FPGA-based transformations. / Timchenko L. and etc. // Information Technology in Medical Diagnostics, CHAPTER – 7. Netherlands. 2017. P. 129-145.

Method of indicators forecasting of biomedical images using a parallel-hierarchical network / Timchenko L. and etc. // Proceedings of SPIE - The International Society for Optical Engineering. 2019. DOI: 10.1117/12.2536808

Timchenko L., Wójcik W., Kokriatskaia N. Architecture of the parallel hierarchical network for fast image recognition // Proceedings of SPIE - The International Society for Optical Engineering. 2016. DOI: 10.1117/12.2249340

Precision measurement of coordinates of power center of extended laser path images, / Timchenko L. and etc. Proc. SPIE 10808, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments. 2018. DOI: 10.1117/12.2501628

Parallel-hierarchical processing and classification of laser beam profile images based on the GPU-oriented architecture / Yarovyi A. and etc. Proc. SPIE 10445, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments. 2017. DOI: 10.1117/12.2280975

REFERENCES

Nakonechna S. (2014). Obroblennya zobrazhen' plyam lazernih puchkіv іz zastosuvannyam paralel'no-ієrarhіchnih merezh [Image processing of laser beam spots using parallel-hierarchical networks] Extended abstract of candidate’s thesis. Lviv [in Ukrainian].

Saldaña-Heredia A., Márquez-Aguilar P., Lara A., Molina-Ocampo A. (2020). Digital Image Processing Applied to Optical Measurements. London. DOI: 10.5772/intechopen.88704

Timchenko L, Pijarski P, Zavadskiy V. (2016). Processing laser beam spot images using the parallel-hierarchical network for classification and forecasting their energy center coordinates. DOI: 10.1117/12.2248878

Stepaniuk D. (2018). Metod prognozuvannya pokaznikіv bіomedichnih zobrazhen' z vikoristannyam paralel'no-ієrarhіchnoї merezhі [Method of forecasting indicators of biomedical images using a parallel-hierarchical network]. Donetsk [in Ukrainian]. DOI: 10.31474/1996-1588-2018-1-26-101-105

Timchenko L., Kokryatska N., Babiuk N. (2014). Metod klasifіkacії zobrazhen' plyam lazernih puchkіv іz zastosuvannyam paralel'no-ієrarhіchnoї merezhі іz pіdvishchenoyu tochnіstyu [The method of classification of images of spots of laser beams with use of a parallel-hierarchical network with the increased accuracy]. [in Ukrainian].

Timchenko L., Hertsii O., Kokryatska N., Halushko M. (2017). Metod vimіryuvannya koordinat energetichnogo centru zobrazhen' protyazhnih lazernih tras [Method of measuring the coordinates of the energy center of images of long laser paths]. Kiyv [in Ukrainian].

Timchenko L., Zlepko M. (2017). Modified method of parallel-hierarchical network teaching based on population Coding. Netherlands.

Timchenko L., Nakonechna S. (2014). Obroblennya zobrazhen' plyam lazernih puchkіv іz zastosuvannyam paralel'no-ієrarhіchnih merezh [Image processing of laser beam spots using parallel-hierarchical networks]. [in Ukrainian]. DOI: 10.15587/2313-8416.2014.27537

Tymchenko L., Tverdomed V., Petrovsky N., Kokryatska N., Maistrenko Y. (2019). Development of a method of processing images of laser beam bands with the use of parallel hierarchic networks. DOI: 10.15587/1729-4061.2019.188568

Kuang Z., Li J., Edwardson S., Walter P., Liu D., Dearden G. (2015). Ultrafast laser beam shaping for material processing at imaging plane by geometric phase masks using a spatial light modulator. London. DOI: https://doi.org/10.1016/j.optlaseng.2015.02.004

Tang Y. Li J. Zhou T. Schille J. (2018). Dynamic beam shaping with polarization control at the image plane for material processing. Liverpool. DOI: https://doi.org/10.1016/j.procir.2018.08.083

Timchenko L., Petrovskiy N., Kokryatskaya N., Yarovyi A. (2017). Processing laser beam images using parallelhierarchical FPGA-based transformations. Netherlands.

Timchenko L., Kokriatskaia N., Pavlov V, Dzierzak R., Amirgaliyeva S. (2019). Method of indicators forecasting of biomedical images using a parallel-hierarchical. DOI: 10.1117/12.2536808

Timchenko L, Wójcik W, Kokriatskaia N. (2016). Architecture of the parallel hierarchical network for fast image. DOI: 10.1117/12.2249340

Timchenko L., Pavlov S., Kokriatskaia N., Gertsiy O., Stepaniuk D., Babiuk N., Kashaganova G., Harasim D. (2018). Precision measurement of coordinates of power center of extended laser path. DOI: 10.1117/12.2501628

Yarovyi A., Timchenko L., Kozhemiako V., Kokriatskaia N. (2017). Parallel-hierarchical processing and classification of laser beam profile images based on the GPU-oriented architecture. DOI: 10.1117/12.2280975

Published

2021-07-05

How to Cite

Tymchenko, L., Kokryatska, N., Tykhonov, A., & Dubova, N. (2021). DEVELOPMENT OF MATHEMATICAL MODELS OF PARALLELHIERARCHICAL TRANSFORMATION FOR EFFICIENT IMAGE PROCESSING. Transport Systems and Technologies, (37), 156–164. https://doi.org/10.32703/2617-9040-2021-37-15