The paper focuses on key scientific and academic accomplishments of Sergei Borisovich Popov, Doctor of Engineering. In 1981, S.B. Popov graduated the Faculty of Systems Engineering of Kuibyshev Aviation Institute named after academician S.P. Korolyov (KuAI, currently - S.P. Korolyov Samara National Research University) majoring in Applied Mathematics. He worked at KuAI from 1981 (in 1992 the Institute was renamed into S.P. Korolyov Samara State Aerospace University, SSAU) first in the capacity of an engineer and then - a senior engineer and a junior researcher. From January 1993 till December 1998, he worked in the capacity of a teaching assistant at the Department of Engineering Cybernetics at S.P. Korolyov Samara State Aerospace University (SSAU, formerly KuAI). His graduate thesis was related to the research in which he was engaged over a long period of his activity and to which he still continues to pay much attention, i.e. scientific research automation using computer vision techniques. Within the framework of joint activities with A Department of Lebedev Physical Institute of the USSR Academy of Sciences (LPI RAS), he has developed new software for the Automated control system for spherical optical surfaces (ACSOS) "Shadow" [1, 2]. Being a part of the Research and Development Laboratory of KuAI-SSAU, he participated in the development of algorithmic and software support of the image processing system based on the PC image processing automated system [3-6]. In his research S.B. Popov developed methods of efficient organization of computing processes in image processing which paralleled these processes by combining sequence image operations into a pipeline [7-9]. These studies provided the basis for his Ph.D. thesis in Engineering “Modeling of Data Stream Processing Networks and Methods of Organizing Two-Dimensional Data Sets in Image Processing.” The thesis has presented efficient methods of image stream processing in PC-based computing systems and developed image processing software tools based thereon combining high performance of Big Data processing, relatively low value, scalability, feasibility in development and implementation of new software modules, and high adjustability to different formats of storing images. The Candidate degree in Engineering was conferred by the Dissertation Council of S.P. Korolyov Samara State Aerospace University (SSAU) on May 15, 1998 and approved by the State Higher Attestation Committee of the Russian Federation on November 20, 1998.
High-Performance Computing / V.O. Sokolov
Additionally, S.B. Popov is fully engaged in developing automation systems for complex research and tests, and in building original computer vision systems both in traditional applications (for recognition of identification numbers of railway tanks) and for unique laboratory investigations [26, 27].
In particular, under the guidance and with the active involvement of S. B. Popov, the following software tools have been developed: Automated System of Data Control, Collection and Processing in Experiments in a Wind Tunnel with a Climate chamber dynamometer in the Technical Development Directorate of JSC AVTOVAZ (Togliatti, 2002-2003), Railway Tanks Registration System in Samara-Terminal Ltd. (Syzran, 2004-2005), Computer Vision System to Control Laboratory Analysis on Quantifying Gel Particles in Polymer Solution in Kuibyshevazot сompany (Togliatti, 2005), Automated Computer Vision System to Control Identification Numbers of Tank Wagons in JSC Ufa Refinery (Ufa, 2008-2009), and up-grading a control system with an all-wheel drive chassis dynamometer system by Schenck in a wind tunnel (2012) for the Research and Development Centre of JSC AVTOVAZ (Togliatti).
Scientific tasks for building mathematical models and control algorithms for the all-wheel drive chassis dynamometer system by Schenck [28] and complex humidity- and temperature-control systems, being a part of the wind tunnel for testing light motor vehicles, LCVs and minivans, have been successfully solved in applications developed for the Research and Development Centre of JSC AVTOVAZ.
When creating computer vision systems for Samara-Terminal and Ufa Refinery, some original algorithms have been developed for recognition of identification numbers [29, 30] on such complex moving objects as tank wagons for transportation of contaminated crude oil and fuel oil under daylight and artificial daylight conditions with significant changes in surveillance parameters within 24 hours and throughout the year depending on a season [31-34].
New methods of thresholding and analysis of binary images being obtained therewith have been developed for the computer vision system required for laboratory tests on quantifying gel particles in polymer solution for Kuibyshevazot company that operate under conditions of a weak image-contrast ratio and in presence of considerable disturbances [26, 35]. The system used instead of an observer while carrying-out this analysis has reduced dramatically a psychovisual load on lab staff, provided documenting capability of performed lab testing, and improved accuracy and certainly of quantifying gel particles in polymer solution that finally helped adjust a process of manufacturing industrial threads and cord fabrics.
The successful implementation and long-term operation of the above mentioned computer vision systems [36, 37] are based on a human-operator base priority principle. Computer vision capacity provided therein doesn’t remove the operator out of the system, but it makes him released from stress associated with the fear not to notice anything or not to manage with fixing an important event in monitoring a long-lasting dynamic process, thus providing a convenient environment for visual control and editing of an automatically generated list of tanks or fragments of occurring inhomogenuity of the laboratory analysis process.
Projects designed with the involvement of S.B. Popov have found use and successfully operated in the Central Specialized Design Bureau “Progress,” FIAT Research Center (Italy), Intel (USA), and LG (South Korea) and are currently used in academic activities of Samara University.
In his scientific research S. B. Popov brings up one of the most important issues in using IT-equipment – mapping of computational mathematics problems onto the architecture of computing systems which was identified by academician G.I. Marchuk as a fundamental academic research area briefly called a mapping issue.
In particular, solving the issue of imaging computational problems onto the parallel or distributed architecture of computing systems is the most relevant issue since a focus area in improving the efficiency of the use of computing facilities is the use of parallel computing techniques [38]. The basic approach to solve the imaging issue is the analysis of a computational problem that identifies parallelism and opportunity to use distributed data and is performed on the basis of mathematically equivalent transformations of an information structure model of the solution algorithm for the problem being investigated or, more generally, of an IT model for solving the problem.
Particularly this very approach was used by S.B. Popov [39, 40] in his Doctoral thesis “Modeling and development of the structure of distributed large-size image processing systems based on the dynamic organization of data” in profile 05.13.18 – Mathematical Modeling, Numerical Computing and Software Systems (consultant – Corresponding Member of the RAS V.A. Soifer [41]), which was successfully defended at the end of 2010 in the Dissertation Council of SSAU. The thesis based on the dynamic management method, processing iterator models, and equivalence transformation rules has solved the problem of modeling and structuring of distributed image processing systems with different types of parallelism. A set of obtained scientific results is to be the solution of the fundamental scientific problem – the mapping issue for a widely used class of problems of mathematical image processing. He took his Doctoral degree in Engineering in 2011.
For the time being, in his papers S. B. Popov investigates characteristic features of the Earth’s remote sensing data in the frame of Big Data and new opportunities, challenges, and research areas arising therefrom [42], considers advantages of using the Big Data technique when building distributed systems for processing multidimensional spatially dependent data, in particular, transparent expansion of functionality of such systems and improvement of their quality [43], and definition of new smart properties [44].
S.B. Popov took part in implementation of dozens of grants, state-financed and contractual research projects and was an authorized person responsible for several large research and development projects. He is also a leader of some grants financed by the Russian Foundation for Basic Research.
The projects designed with the involvement of S.B. Popov were exhibited at the Russian National Exhibition in China (November 8-13, 2006, Beijing) and were awarded with certificates of the First and Third District Exhibitions of Business Angels and Innovators (2003 – Nizhny Novgorod, 2005 – Samara).
High-Performance Computing / V.O. Sokolov
He is the author or co-author of more than 100 research papers, including three monographs and 25 articles in the leading journals, such as Technical Physics, Automation in Industry, Pattern Recognition and Image Analysis, Computer Optics, etc., and 5 invention certificates received. S. B. Popov is one of the most active reviewers of the scientific journal “Computer Optics” [45, 46]. Besides, thanks to his efforts and based on the results in 2015, the journal has joined the rank of the best half (the second quartile) of the journals indexed in the Scopus database in its all focus areas.
In 2013, S. B. Popov was awarded with the Letter of Acknowledgement of Samara Regional Duma (regional legislative body) “For Strong Contribution to Development of the Federal State Budgetary Institution of Education – Image Processing Systems Institute of the RAS.”
Popov S.B. was the winner of the regional Science and Technology Award in 2014 for his research work "Development of computer vision systems for the automation of high-tech manufacturing and logistics facilities in Samara Region".
S.B. Popov successfully continues his employment at the academic institute alongside with his teaching activities – from January 1999 he was also employed as an assistant professor of the Department of Engineering Cybernetics, SSAU, and since 2011 he has been working in the capacity of a professor of the Department of Engineering Cybernetics, SSAU.
He was awarded with the academic title of an associate professor of the Department of Engineering Cybernetics, SSAU, in accordance with the order of the Federal Education and Science Supervision Service of the Russian Federation dated 26 October 2006 No. 2212/1179-D.
S. B. Popov pays great attention to students and young researchers’ engagement in scientific activities; the diploma theses of his advised students were recognized as the best ones many times [6, 47].
In particular, he (co-authored) has written five chapters of the monograph “Methods of Computer Image Processing” successfully gone into two editions in 2001 and 2003 [48] in the Publishing House “Fizmatlit” (Moscow) and recommended by the Ministry of Education of the Russian Federation as a study guide for students who learn Applied Mathematics. In 2010, the monograph was supplemented with new chapters and translated into English [49, 50].
In 2006, on request of the SSAU’s Innovative Educational Program “Development of the Center of Excellence and Training of World-Class Specialists in Aerospace and Geoinformation Technologies” implemented within the framework of the Education National Priority Project, 4 manuals for graduate students were published [51-54].
New lecture courses developed at different times, such as Network Programming Techniques, Parallel Programming, Parallel Programming Software Tools and Technologies, Data Mining, Big Data Processing Methods and Techniques (in the framework of the Professional Development Programme) should be noted, too.
In conclusion, I would like to wish Sergei Borisovich Popov good health, high performance, and talented students in order to continue his research and to obtain new results!
High-Performance Computing / V.O. Sokolov
[4] Arefyev EYu, Bagbaya ID, Ovchinnikov KV, Popov SB, Sisakyan IN, Soifer VA. Experiments on reconstructive tomography using an automated image
processing system. Computer Optics 1987; 2: 31–35. (in Russian)
[5] Arefyev EYu, Golub MA, Ovchinnikov KV, Popov SB, Sisakyan IN, Soifer VA, Tikhonov DN, Khramov AG, Shamalova GV. Verification of the phase
microrelief of computer optics elements. Soviet Physics: Technical physics 1990; 35(6).
[6] Popov SB, Khasanov IA. Investigation of Modifications of Algorithms for Fractal Image Encoding. Pattern Recognition and Image Analysis 1996; 6(
Pattern Recognition and Image Analysis 1996; 6(
Analysis 1998; 8(
Education and High Performance Computing Center. Proceedings of conf. "Telematics 2002", 2002; 162–163. (in Russian) [12] Volotovsky SG, Kazansky NL, Popov SB, Serafimovich PG, Soifer VA, Fursov VA. Methodological aspects of parallel applications development in the field of computer optics and image processing. Proceedings of conf. "Telematics 2002", 2002; 163–165. (in Russian) [13] Kazanskiy NL, Serafimovich PG, Popov SB, Khonina SN. Using guided-mode resonance to design nano-optical spectral transmission filters. Computer
Optics 2010; 34(
Samara: SSAU, 2000. [17] Soifer VA, Sergeyev VV, Popov SB, Myasnikov VV. The theoretical foundations of digital image processing. Samara: SSAU, 2000. (in Russian) [18] Popov SB, Skuratov SA, Fursov VA. Basics for working on a computing cluster. Samara: Samara Scientific Center of RAS & SSAU, 2004. (in Russian) [19] Kazanskiy NL, Popov SB, Serafimovich PG. Organization of computational experiment on high-performance systems. Samara: IPSI RAS, 2010. (in
Russian) [20] Gashnikov MV, Glumov NI, Popov SB, Segreyev VV, Farberov EA. Software System for Transmitting Large-Size Images via the Internet. Pattern
Recognition and Image Analysis 2001; 11(
Optics 2003; 25: 175–182. (in Russian) [22] Nikonorov AV, Popov SB, Fursov VA. The principle of consistency of estimates in the problem of identification of color reproduction models. Computer
Optics 2002; 24: 148–151. (in Russian) [23] Nikonorov AV, Popov SB, Fursov VA. Applying the estimates consistency principle in the problem of identification of color reproduction models.
Proceedings of the Samara Scientific Center of the Russian Academy of Sciences 2002; 4(
Scientific Center of the Russian Academy of Sciences 2003; 5(
(in Russian) [27] Abulhanov SR, Popov SB, Ivliev NA, Podlipnov VV. Device for Control of Apertures Surface of Pipes of Oil Assortment. Procedia Engineering 2017; 176: 645–652. [28] Ignatov NA, Kazansky NL, Kornev YuA, Popov SB. Modeling of dynamometer control system. Journal of Samara State Technical University, Ser.
Physical and Mathematical Sciences 2005; 38: 115–121. (in Russian)
[29] Volotovskii SG, Kazanskiy NL, Popov SB, Khmelev RV. Recognition of the numbers of railway tanks using fast localization and modification of the
algorithm for comparing an object with a template using the Hausdorff metric. Survey of Applied and Industrial Mathematics 2005; 12(
Modified Correlator in the Hausdorf Metric. Computer Optics 2005; 27: 177–184. (in Russian) [31] Bulanov AP, Volotovskii SG, Kazanskiy NL, Popov SB, Khmelev RV, Shumakov SM. Vision System for Registration of Railway Tank-cars. Automation in industry 2005; 6: 57–59. (in Russian) [32] Volotovskii SG, Kazanskii NL, Popov SB, Khmelev RV. Machine Vision System for Registration of Oil Tank Wagons. Pattern Recognition and Image
Analysis 2005; 15(
Analysis 2015; 25(
DOI:10.1117/12.928441. [41] Sokolov VO. On the 70th birthday of corresponding member of the Russian academy of sciences Victor A. Soifer. CEUR Workshop Proceedings 2015; 1490: 1–8. [42] Popov SB. The Big Data methodology in computer vision systems. CEUR Workshop Proceedings, 2015; 1490: 420–425. DOI: 10.18287/1613-0073-20151490-420-425. [43] Protsenko VI, Seraphimovich PG, Popov SB, Kazanskiy NL. Software and hardware infrastructure for data stream processing. CEUR Workshop
Proceedings, 2016; 1638: 782–787. DOI: 10.18287/1613-0073-2016-1638-782-787.
[44] Ilyasova NYu, Kupriyanov AV, Popov SB, Paringer RA. Particular usage characteristics of BIG DATA in medical diagnostics tasks. Highly available
systems 2016; 12(
High-Performance Computing / V.O. Sokolov [45] Kolomiets EI. Analysis of activity of the scientific journal Computer Optics. CEUR Workshop Proceedings 2015; 1490: 138–150. [46] Sokolov VO. Contribution of Samara scientists into Computer Optics journal development. CEUR Workshop Proceedings 2016; 1638: 194–206. DOI: 10.18287/1613-0073-2016-1638-194-206. [47] Nikonorov AV, Popov SB. Comparative analysis of color reproduction models in offset color printing. Computer Optics 2002; 23: 79–83. (in Russian) [48] Methods of computer image processing. Ed by Soifer VA. Moscow: “Fizmatlit” Publisher; 2003. (in Russian) [49] Myasnikov VV, Popov SB, Sergeyev VV, Soifer VA. Computer Image Processing, Part I: Basic concepts and theory. Ed by Victor A. VDM Verlag, 2010. [50] Gashnikov MV, Glumov NI, Popov SB, Sergeyev VV. Image Compression. Computer Image Processing, Part II: Methods and algorithms. Ed by Soifer
VA. VDM Verlag, 2010: 87–160. [51] Introduction to digital signal and image processing: Mathematical models of images. Ed by Soifer VA. Samara: SSAU, 2006. (in Russian) [52] Introduction to digital signal and image processing: Criteria for image quality and error of image discrete representation. Ed by Soifer VA. Samara: SSAU, 2006. (in Russian) [53] Introduction to digital signal and image processing: Improving the quality and estimation of geometric parameters of images. Ed by Soifer VA. Samara:
SSAU, 2006. (in Russian) [54] Sergeyev VV, Gashnikov MV, Glumov NI, Popov SB. Methods of compression of digital signals and images. Samara: SSAU, 2006. (in Russian)