Comparative analysis of function approximation methods applied to image processing

Application of nonlinear methods of multivariate regression approximation (neural networks, functions linear in fitting parameters, and hierarchical approximation) is considered to problems of image filtering based on a priori information in the form of matched pairs of images (“ideal” and “degraded”). The methods are compared with regard to their efficiency. Vasilii N. Kopenkov. Born 1978. Graduated from the Samara State Aerospace University (SSAU) in 2001. Assistant Professor at the Chair of Geoinformatics, SSAU, and a Junior Researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing and pattern recognition. Author of four papers. Member of the Russian Federation Association for Pattern Recognition and Image Analysis. Andrei V. Chernov. Born 1975. Graduated from the Samara State Aerospace University (SSAU) in 1998. Received candidate’s degree (Cand. Sc. (Eng.)) in 2004. Assistant Professor at the Chair of Geoinformatics, SSAU, and a Researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing, pattern recognition, and geoinformation systems. Author of more than 50 publications, including 11 papers in journals, and a co-author of a monograph. Member of the Russian Federation Association for Pattern Recognition and Image Analysis. Vladislav V. Sergeev. Born 1951. Graduated from the Kuibyshev Aviation Institute (now, the Samara State Aerospace University). Received doctoral degree (Dr. Sc. (Eng.)) in 1993. Head of Laboratory of Mathematical Methods of Image Processing, Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: digital signal processing, image analysis, pattern recognition, and geoinformatics. Author of more than 150 publications, including about 40 papers in journals, and a co-author of 2 monographs. Chair of the Volga-region Branch of the Russian Federation Association for Pattern Recognition and Image Analysis. Corresponding Member of the Russian Ecological Academy and the Russian Academy of Engineering, member of SPIE (The International Society for Optical Engineering), a winner of the Samara District Award for Science and Engineering.     

Software environment for simulating algorithms for image analysis and processing

We consider the purpose, functionality, configuration, and structure of a software environment designed for simulation and investigation of methods, algorithms, and information technology for digital images analysis and processing. Mikhail V. Gashnikov. Born 1975. Graduated from the Samara State Airspace University (SSAU) in 1998. Received candidate’s degree in Technology in 2004. He is now an assistant professor at the chair of earth information of the SSAU. Scientific interests: image processing, compression, statistical coding. Author of more than 30 publications, including 12 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis. Evgenii V. Myasnikov. Born 1981. Graduated from the Samara State Airspace University in 2004. He is now a post-graduate student at the Chair of Earth Information of the Samara State Airspace University. Scientific interests: development of software systems, image processing, image retrieval in databases. Author of 6 publications, including one paper. Member of the Russian Association for Pattern Recognition and Image Analysis. Andrei V. Chernov. Born 1975. Graduated from the Samara State Airspace University (SSAU) in 1998. Received candidate’s degree in Technology in 2004. He is now an assistant professor at the Chair of Earth Information of the SSAU and a research fellow at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing, pattern recognition, geoinformation systems. Author of more than 50 publications, including 11 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis. Nikolai I. Glumov. Born 1962. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1985. Received candidate’s degree in Technology in 1994. He is now a senior researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing and pattern recognition, compression of images, simulation of systems of digital image formation. Author of more than 50 publications, including 21 papers and one monographs (in coauthorsip). Member of the Russian Association for Pattern Recognition and Image Analysis. Vladislav V. Sergeev. Born 1951. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1974. Received doctoral degree in Technology in 1993. Head of the Laboratory of Mathematical Methods for Image Processing at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: digital signal processing, image analysis, pattern recognition, earth information. Author of more than 150 publications, including approximately 40 papers and two monographs (in coauthorship). President of the Povolzh’e Branch of the Russian Association for Pattern Recognition and Image Analysis. Corresponding member of the Russian Ecological Academy and of the Russian Academy of Engineering Sciences. Member of the International Society for Optical Engineering. A laureate of the Samara Provincial Government prize in science and engineering. Marina A. Chicheva. Born 1964. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1987. Received candidate’s degree in Technology in 1998. She is now a senior researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image recognition, compression, fast algorithms for discrete transformations. Author of more than 40 publications, including 15 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis.     

An approximation-based approach to computing image moment invariants

A fast method for computing Hu’s image moment invariants is described. The invariants are found by approximation using generalized moments computed in a sliding window by a parallel recursive algorithm. The proposed method is shown to be computationally more efficient than direct computation. Vladislav V. Sergeev. Born 1951. Graduated from the Kuibyshev Aviation Institute (now, the Samara State Aerospace University) in 1974. Received doctoral degree (Dr. Sc. (Eng.)) in 1993. Head of Laboratory of Mathematical Methods of Image Processing, Image Processing Systems Institute, Russian Academy of Sciences. Scientific interests: digital signal processing, image analysis, pattern recognition, and geoinformatics. Author of more than 150 publications, including about 40 papers in journals, and a co-author of 2 monographs. Chair of the Volga-region Branch of the Russian Federation Association for Pattern Recognition and Image Analysis. Corresponding Member of the Russian Ecological Academy and the Russian Academy of Engineering, member of SPIE (The International Society for Optical Engineering), a winner of the Samara District Award for Science and Engineering. Ol’ga A. Titova. Born 1980. Graduated from the Samara State Aerospace University (SSAU) in 2002. Currently post-graduate student at the Chair of Geoinformatics, SSAU. Scientific interests: image analysis, pattern recognition, fast algorithms of digital image processing, and geoinformatics. Author of nine publications including three papers in journals. Member of the Russian Federation Association for Pattern Recognition and Image Analysis.     

Compression of 3D digital signals based on hierarchical grid interpolation

A method of hierarchical compression of 3D digital signals is considered as a generalization of the familiar image compression method based on the hierarchical grid interpolation to the 3D case. Special attention is paid to constructing 3D interpolation systems. The effectiveness of the method developed here is compared to the prototype using only 2D dependences. Bavrina Alina Yur’evna (b. 1980) graduated from the Samara State Aerospace University (SSAU) in 2003. At present, she is a research scholar at the department of Geoinformatics, SSAU. Her scientific interests include image processing, compression, and geoinformatics. A.Yu.Bavrina has more than 10 publications, including 4 articles. She is a member of the Russian Association for Image Recognition and Analysis. Gashnikov Mikhail Valer’evich (b. 1975) graduated from the Samara State Aerospace University (SSAU) in 1998. In 2004, he defended his Ph.D. (Eng.) thesis. At present, M.V. Gashnikov is an associate lecturer at the Department of Geoinformatics (SSAU). The scope of his scientific interests includes image processing, compression, and statistical coding. He has 30 publications, including 12 papers and a monograph (with coauthors). M.V. Gashnikov is a member of the Russian Association for Image Recognition and Analysis. Sergeyev Vladislav Viktorovich (b. 1951) graduated from the Kuibyshev Aviation Institute (now Samara State Aerospace University) in 1974. In 1993, he defended his D.Sc. (eng.) thesis. At present, V.V. Sergeyev heads the Laboratory of Mathematical Methods of Image Processing at the Institute of Image Processing Systems, Russian Academy of Sciences. His scientific interests include digital signal processing, image analysis, image recognition, and geoinformatics. He has more than 150 publications, including 40 articles and two monographs (with co-authors). V.V. Sergeyev is the chairman of the Povolzh’e Division of the Russian Association for Pattern Recognition and Image Analysis and a Corresponding Member of the Russian Academy of Ecology and the Academy of Engineering Sciences of the Russian Federation, a member of SPIE (International Society for Optical Engineering), and a winner of the Samara Regional Award in Science and Engineering.     

Program and research system for the recognition of individuals by photos of faces on documents

In this article, the developed program and research system for recognizing individuals based on photos of faces on documents is described. The requirements for the system made at the development stage are determined. The most important of these requirements is the possibility of carrying out the investigations of various algorithms with the purpose of the comparing their efficiency, determining their optimum parameters, and selecting the best system of signs. The composition and destination of the main components of the program and research system for recognizing individuals are presented. The main feature of implementation is the use of processing scenarios in the system performed by an interpreter and the presence of an expanded set of the elemental processing functions. This solution results in the rapid development and variation of various algorithms of image processing, formation of signs, and classification. Evgenii Valer’evich Myasnikov. Born in 1981. In 2004, he graduated the Samara State Aerospace University (SGAU) and entered the Post-Graduate Education of SGAU. In 2007, Myasnikov defended the Candidate of Science (Engineering) Dissertation. Currently, he works as the Probationer Researcher at the Image Processing Systems Institute, Russian Academy of Sciences and simultaneously as the Assistant of the Department of Geoinformatics at SCAU. The circle of scientific interests involves the creation of software complexes, image processing, and pattern recognition, and search for images in databases. Myasnikov has 23 publications, including six articles. He is the member of the Russian Association of Pattern Recognition and Image Processing. Vladislav Viktorovich Sergeev. Born in 1951. In 1974, he graduated the Kuibyshev Aviation Institute (now, the Samara State Aerospace University). In 1994, he defended his Doctor of Science (Engineering) dissertation. Currently, he works at the Chief of Laboratory of Mathematical Methods of Image Processing at the Image Processing Systems Institute, Russian Academy of Sciences. The circle of scientific interests involves the digital processing of signals, analysis of images, pattern recognition, and geoinformatics. Sergeev has more than 200 publications, including about 40 articles and two monographs (in partnership). Sergeev is the Chairman of the Povolzh’e Division of the Russian Association of Pattern Recognition and Image Analysis. He is the Corresponding Member of the Russian Environmental Academy and Academy of the Engineering Sciences of the Russian Federation, the member of SPIE (the International Society for Optical Engineering), and the Laureate of the Samara Regional Prize in the Field of Science and Engineering. Nikolai Ivanovich Glumov. Born in 1962. In 1985, he graduated the Kuibyshev Aviation Institute (now, the Samara State Aerospace University). In 1994, he defended the Candidate of Science (Engineering) Dissertation. Currently, he is working as the Senior Researcher at the Image Processing Institute, Russian Academy of Sciences. The circle of scientific interests involves the image processing and pattern recognition, image compression, and simulation of the systems of formation of digital images. Glumov has more than 90 publications, including more than 30 articles and one monograph (in partnership). He is the member of the Russian Association of Pattern Recognition and Image Processing. Aleksandr Pavlovich Chikhonadskikh. Born in 1959. In 1981, he graduated the Mozhaiskii Military Space Engineering Institute (now, the Mozhaiskii Military Space Engineering Academy). In 1988, he defended the Candidate of Science (Engineering) Dissertation. Currently, he is working as the Chief of the Second Research Department at the FGUP State Research Institute of Applied Problems. The circle of scientific interests involves the creation of program-apparatus complexes, digital processing of signals, analysis of images, and pattern recognition. Chikhonadskikh has more than 70 publications, including three articles and three monographs (two in partnership). Aleksandr Viktorovich Koryakin. Born in 1959. In 1982, he graduated the Dnepropetrovsk State University. In 2002, he defended the Doctor of Science (Engineering) Dissertation. Currently, he is working as the Senior Researcher at the FGUP State Research Institute of Applied Problems. The circle of scientific interests involves the digital processing of signals, analysis of images, pattern recognition, and creation of software-apparatus complexes. Koryakin has more than 100 publications, including three monographs. Inga Yur’evna Terent’eva. Born in 1978. In 2000, she graduated the North-West Academy of State Service (St. Petersburg), and in 2004, she graduated the Post-Graduate Education at the Institute of the Human Brain, Russian Academy of Sciences. In 2005, she defended the Candidate of Science (Psychological) Dissertation. Currently, she is working as the Chief of Laboratory at the FGUP State Research Institute of Applied Problems. The circle of scientific interests involves the analysis of biometric data, pattern recognition, and neural networks. Terent’eva has 23 publications, including eight articles.     

Fast correlation method with the use of a wide selection of template in problems of image analysis

The problem of searching for and recognizing fragments of images that correspond to one of a wide variety of template is considered. The method of the fast correlation of a wide selection of trinary template, which successfully resolves this problem, is suggested. The use of this method in two problems of image analysis is shown, namely, the search for position of eyes in documental photographs of faces and the recognition of computer-readable lines in scanned images of documents. Nikolai Ivanovich Glumov. Born in 1962. In 1985, he graduated the Kuibyshev Aviation Institute (now, the Samara State Aerospace University). In 1994, he defended the Candidate of Science (Engineering) Dissertation. Currently, he is working as the Senior Researcher at the Image Processing Systems Institute, Russian Academy of Sciences. His circle of scientific interests involves the image processing and pattern recognition, image compression, and simulation of the systems of formation of digital images. Glumov has more than 90 publications involving more than 30 articles and one monograph (in partnership). He is a member of the Russian Association of Pattern Recognition and Image Processing. Evgenii Valer’evich Myasnikov. Born in 1981. In 2004, he graduated the Samara State Aerospace University and entered the Post-Graduate Education of SGAU. In 2007, Myasnikov defended the Candidate of Science (Engineering) Dissertation. Currently, is working as the Probationer Researcher at the Image Processing Systems Institute, Russian Academy of Sciences and simultaneously as the Assistant of the Department of Geoinformatics at SCAU. The circle of scientific interests involves the creation of software complexes, image processing and pattern recognition, and search for images in databases. Myasnikov has 23 publications, including six articles. He is the member of the Russian Association of Pattern Recognition and Image Processing. Vasilii Nikolaevich Kopenkov. Born in 1978. In 2001, he graduated the Samara State Aerospace University (SGAU). Currently, he is working as the assistant of the Department of Geoinformatics at the SGAU and Junior Researcher at the Image Processing Systems Institute, Russian Academy of Sciences. The circle of scientific interests involves the processing of images of the distanced probing of the Earth, pattern recognition, and geoinformatic systems. Kopenkov has 17 publications, including seven articles. He is the member of the Russian Association of Pattern Recognition and Image Processing. Marina Aleksandrovna Chicheva. Born in 1964. In 1987, she graduated the Kuibyshev Aviation Institute (now, the Samara State Aerospace University). In 1998, she defended the Candidate of Science (Engineering) Dissertation. She currently works as the Senior Researcher at the Image Processing Systems Institute, Russian Academy of Sciences. Her scientific interests include image processing and compression, rapid algorithms of discrete transformations, and pattern recognition. Chicheva has more than 18 articles, including one monograph (in partnership). She is the member of the Russian Association of Pattern Recognition and Image Processing.     

Parallel algorithms for a hypercomplex discrete fourier transform

Methods for the parallel computation of a multidimensional hypercomplex discrete Fourier transform (HDFT) are considered. The basic idea consists in the application of the properties of the hypercomplex algebra in which this transform is performed. Additional possibilities for increasing the efficiency of the algorithm are provided by the natural parallelism of the multidimensional Cooley-Tukey scheme. Marat Vyacheslavovich Aliev. Born 1978. Graduated from the Adygeya State University in 2000. Received candidate’s degree in physics and mathematics in 2004. Presently he is a senior lecturer at the Department of Applied Mathematics and Information Technologies, Adygeya State University. Scientific interests: image processing, fractals, fast algorithms of discrete transforms, and finite-dimensional algebras. Author of 14 publications, including 7 papers. Member of the Russian Association of Pattern Recognition and Image Analysis. Aleksandr Mikhailovich Belov. Born 1980. Graduated from the Samara State Aerospace University in 2002. In the same year, he entered postgraduate courses with the specialty 05.13.18: mathematical modeling, numerical methods, and program complexes. Presently he is a postgraduate student at the Department of Geoinformatics, Samara State Aerospace University, and a trainee at the Laboratory of Mathematical Methods of Image Processing, Image Processing Systems Institute, Russian Academy of Sciences. Scientific interests: discrete orthogonal transforms, fast algorithms of discrete orthogonal transforms, and theory of canonical systems of calculus. Author of 13 publications, including 5 papers. Member of the Russian Association of Pattern Recognition and Image Analysis. Aleksei Vladimirovich Ershov. Born 1983. In 2000, he graduated from the Samara Lyceum of Economics and entered the Faculty of Mechanics and Mathematics, Samara State University, to specialize in the field of Organization and Technology of Information Security. In 2001, he started his training within an additional educational program and was qualified as a translator in the field of professional communication. Presently he is a fifth-year student at Samara State University. The title of his diploma work is “Control of the Flows of Confidential Information.” He is an active participant in the translation of the monograph Principia Mathematica, Cambridge University Press, 1927, by A. Whitehead and B. Russell. Author of four publications, including two papers. Marina Aleksandrovna Chicheva. Born 1964. Graduated from the Kuibyshev Aviation Institute (now Samara State Aerospace University) in 1987. Received candidate’s degree in Engineering in 1998. Presently she is a senior researcher at the Image Processing Systems Institute, Russian Academy of Sciences. Scientific interests: image processing, compression, and fast algorithms of discrete transforms. Author of more than 50 publications, including 18 papers and 1 monograph. Member of the Russian Association of Pattern Recognition and Image Analysis.     

Stabilization of the compressed data formation rate in hierarchical image compression

A new method is proposed for stabilizing the rate of compressed data formation in the case of hierarchical image compression. The method is based on using various values of the control parameter (maximum error) for various scale levels of image representation and for error correction at the last level depending on the received compressed information content. Gashnikov Mikhail Valer’evich (b. 1975) graduated from the Samara State Aerospace University (SSAU) in 1998. In 2004, he defended his Ph.D. thesis in engineering. At present, Gashnikov is an associate lecturer at the Department of Geoinformatics (SSAU). The scope of his scientific interests includes image processing, compression, and statistical coding. He has 30 publications, including 12 papers and a monograph (with co-authors). He is a member of the Russian Association for Image Recognition and Analysis. Glumov Nikolai Ivanovich (b. 1962) graduated from the Kuibyshev Aviation Institute (now Samara State Aerospace University) in 1985. In 1994, he defended his Ph.D. thesis in engineering. At present, Glumov is a senior scientist at the Institute of Image Processing Systems, Russian Academy of Sciences. His scientific interests include image processing and recognition, image compression, and simulation of digital image formation systems. He has more than 60 publications, including 20 articles and a monograph (with co-authors). He is a member of the Russian Association of Image Recognition and Analysis. Sergeyev Vladislav Viktorovich (b. 1951) graduated from the Kuibyshev Aviation Institute (now Samara State Aerospace University) in 1974. In 1993, he defended his D.Sc. (eng.) thesis. At present, V.V. Sergeyev heads the Laboratory of Mathematical Methods of Image Processing at the Institute of Image Processing Systems, Russian Academy of Sciences. His scientific interests include digital signal processing, image analysis, image recognition, and geoinformatics. He has more than 150 publications, including 40 articles and two monographs (with co-authors). V.V. Sergeyev is the chairman of the Povolzh’e Division of the Russian Association for Pattern Recognition and Image Analysis and a Corresponding Member of the Russian Academy of Ecology and the Academy of Engineering Sciences of the Russian Federation, a member of SPIE (International Society for Optical Engineering), and a winner of the Samara Regional Award in Science and Engineering.     

Statistical methods for detecting latent periodicity patterns in biological sequences: The case of small-size samples

An original spectral-statistical approach for detecting latent periodicity in biological sequences is proposed. This approach can be applied under conditions of limited statistical sample. It allows one to avoid redundancy and instability when identifying the latent periodicity structure. The optimality of the periodicity-pattern-size estimates obtained for approximate tandem repeats on the basis of the spectral-statistical approach is demonstrated in practical examples. Maria Borisovna Chaley was born in 1963 and graduated from the Moscow Institute of Physics and Technology in 1988 (M.Sc.). She received her PhD in biophysics in 1993 and became a docent in bioinformatics in 2003. At the present time, she is a senior research fellow at the Institute of Mathematical Biology Problems of the Russian Academy of Sciences. Her research interests include bioinformatics, genetic text analysis, and molecular evolution. She is the author of over 40 research publications, including 14 journal articles. Nafisa Nailovna Nazipova was born in 1960 and graduated from the Department of Computational Mathematics and Cybernetics of Lenin Kazan State University in 1982 (MSc.). She received her PhD in physics and mathematics (mathematic modeling, numerical methods, and program complexes) in 2002. At the present time, she is the head of the bioinformatics laboratory at the Institute of Mathematical Biology Problems of the Russian Academy of Sciences. Her research interests include bioinformatics and the structural and functional organization of genetic sequences. She is the author of over 35 research publications, including 9 papers in refereed journals and 2 book chapters. Vladimir Andreyevich Kutyrkin was born in 1952 and graduated from the Department of Mechanics and Mathematics of Lomonosov Moscow State University in 1974 (MSc.). He received his PhD in physics and mathematics in 1995. At the present time, he is a docent of Bauman Moscow State Technical University. His research interests include applied mathematical statistics, computational and discrete mathematics, and bioinformatics. He is the author of over 20 research publications, including 11 journal papers.     

Fast algorithms for a multidimensional hypercomplex discrete Fourier transform with radix-3 decomposition

Combined algorithms for the multidimensional hypercomplex discrete Fourier transform (HDFT) of a real signal with data representation in the Hamilton-Eisenstein generalized codes are synthesized. The complexity of arithmetic operations in a commutative-associative hypercomplex algebra and its representation in generalized codes are obtained. It is shown that there exist only two essentially different commutative-associative hypercomplex algebras: the direct sums of real or complex algebras. The computational complexity of the algorithm synthesized is estimated. Marat Vyacheslavovich Aliev. Born 1978. Graduated from Adygeya State University in 2000. Received candidate’s degree in physics and mathematics in 2004. Presently he is a senior lecturer at the Department of Applied Mathematics and Information Technologies, Adygeya State University. Scientific interests: image processing, fractals, fast algorithms of discrete transforms, and finite-dimensional algebras. Author of 14 publications, including 7 papers. Member of the Russian Association of Pattern Recognition and Image Analysis. Marina Aleksandrovna Chicheva. Born 1964. Graduated from the Kuibyshev Aviation Institute (now Samara State Aerospace University) in 1987. Received candidate’s degree in Engineering in 1998. Presently, she is a senior researcher at the Image Processing Systems Institute, Russian Academy of Sciences. Scientific interests: image processing, compression, and fast algorithms of discrete transforms. Author of more than 50 publications, including 18 papers and 1 monograph. Member of the Russian Association of Pattern Recognition and Image Analysis.     

Family of models for describing one class of metallographic images

Models for images syntax are developed, tried, and tested in describing the syntax of microstructural metallographic images of wrought aluminum alloys. Gennadii Mikhailovich Tsibul’skii was born in 1947 and graduated from Krasnoyarsk Polytechnic Institute in 1973. Since 1975, he has been involved in the analysis of digital images. In 1978, he completed his postgraduate course at the Lenin Leningrad Electronic Technical Institute. He received his candidate’s degree in 1987 and a doctoral degree in engineering in 2006. He was appointed a professor in 2007. In 1996, he founded the Artificial Intelligence Systems Department and has worked there as a chairman since then. His scientific interests include the multiagent approach to images analysis, and he is the author of more than 70 publications (including one book published by the Siberian Branch of the Russian Academy of Sciences). At present, Gennadii Tsibul’skii is the director of the Space and Information Technologies Institute at Krasnoyarsk Siberian Federal University. Yurii Anatol’evich Maglinest was born 1965 and graduated from Krasnoyarsk Polytechnic Institute in 1973; he then pursued postgraduate studies there. He received his candidate’s degree in engineering in 1996 in the analysis of metallographic images. He is an associate professor at the State Commission for Academic Degrees and Titles of the Russian Federation. At present, he is a chair of the Scientific University Laboratory of Flexible Software Systems at the Artificial Intelligence Systems Department at Krasnoyarsk Siberian Federal University. His scientific interests include aerospace information storage, processing and analysis, and flexible software systems. Dmitrii Al’bertovich Perfil’ev was born in 1968 and graduated from Krasnoyarsk Polytechnic Institute in 1992. Since 2000, he has been specializing in problems in digital images analysis and, in particular, in describing microstructural pictures of aluminum alloys. He received his candidate’s degree in engineering in 2007 and is the author of 8 publications related to the problem in question. At present, he is a researcher and a lecturer at the Artificial Intelligence Systems Department at Krasnoyarsk Siberian Federal University.     

Universal method for controlling maximum error in image compression

A method for controlling the maximum restoration error in image compression is proposed that can be used in combination with the arbitrary methods of compression. The method has been studied for the case of its application together with the standard compression method JPEG. The results have shown that, at equal coefficients of compression, the proposed method substantially reduces the maximum error of image restoration. Sergeev Vladislav Viktorovich. Was born in 1951, in 1974 got his degree from the Kuybyshev Aircraft Institute (now the State Aerospace University of Samara). In 1993 he defended his dissertation to the degree of the Doctor of Technical Sciences. At present he is the Head of the Laboratory of Mathematical Methods of Image Processing at the Institute of the Systems of Image Processing of the Russian Academy of Sciences. The circle of his research interests includes digital processing of signals, analysis of images, pattern recognition, geoinformatics. He has over 200 publications, including about 40 papers, two monographs (in collaboration). He is Chairman of the Volga Division of the Russian Association of Pattern Recognition and Image Analysis. He is a Corresponding Member of the Russian Ecological Academy and the Academy of Engineering Sciences of the RF, a member of the SPIE (International Society for Optical Engineering), prize winner of the Samara Administration Prize in Science and Technology. Timbay Yelena Ivanovna. Was born in 1985. In 2008 got her degree from the Samara State Aerospace University (SSAU). At present she is a technician at the Institute of the Image Processing Systems, RAS. She is engaged in image processing, imag compression. Has 11 publication, including 3 articles.     

Nonparametric pattern recognition systems based on learning a sample decomposition by its dimension

The technique of multilevel nonparametric pattern recognition systems synthesis on the basis of learning sample decomposition principles and parallel computing technology is proposed. This basis provides effective processing of highly dimensional information. Aleksandr Vasil’evich Lapko was born in 1949 and graduated from Frunze Polytechnic Institute in 1971. He has been a doctor of technical sciences since 1990 and a leading researcher at the Institute of Computational Modeling of the Siberian Branch of the Russian Academy of Sciences. His scientific interests include the following: nonparametric statistics, pattern recognition systems, and the design and optimization of indefinite systems. He is the author of 223 publications, including 13 monographs. He is chairman of the Krasnoyarsk regional department of the Pattern Recognition and Image Analysis Association and an Honored Science Worker of the Russian Federation. Vasilii Aleksandrovich Lapko was born in 1974 and graduated from Krasnoyarsk State Technical University in 1996. He has been a doctor of technical sciences since 2004 in systems analysis, management, and information processing. He is a senior researcher at the Institute of Computational Modeling of the Siberian Branch of the Russian Academy of Sciences. His scientific interests include the following: nonparametric statistics, pattern recognition systems, the design of indefinite systems, and collective evaluation methods. He is the author of 105 publications, including 4 monographs. He was awarded by the Russia Academy of Sciences a medal for the best scientific publication in 2005 for young scientists in Informatics, Computer Engineering, and Automation.     

Estimating directions of optic disk blood vessels in retinal images

The problem of determining directions of blood vessels in the optic disk is considered. The proposed method for estimating the vessel directions is based on analyzing local minima of gray-scale profile of the eye-ground image. Results of tests on real images are presented. Mikhail Anan’in. Born 1984. Graduated from the Samara State Aerospace University in 2007 and is currently a post-graduate student at the same university. From 2006 to present is a junior researcher at the Image Processing Systems Institute, Russian Academy of Sciences. Scientific interests: image processing, image reconstruction, pattern recognition, wavelet analysis, and differential geometry. Authored more than ten papers. Nataliya Il’yasova. Born 1966. Graduated from the Samara State Aerospace University in 1991, where in 1997 she received candidate’s degree (Eng.). Currently a senior s researcher at the Image Processing Systems Institute, Russian Academy of Sciences and a senior lecturer at Samara State Aerospace University. Scientific interests: digital image processing and recognition, pattern recognition, information systems in biomedical applications, computer-aided systems for monitoring eye fundus microvascular morphology, and analysis of cardiac coronary vessels. Author of more than 60 papers in the field of image processing and pattern recognition. Aleksandr Kupriyanov. Born 1978. Graduated from the Samara State Aerospace University in 1991 and in 1997 received candidate’s degree (Eng.) from the same university. Currently has a position of researcher at the Image Processing Systems Institute, Russian Academy of Sciences. Scientific interests: digital image processing and recognition, pattern recognition, information systems in biomedical applications, computer-aided systems for monitoring eye fundus microvascular morphology, analysis of cardiac coronary vessels, evaluation of diagnostic features, and retinal image analysis. Author of more than 30 papers in the field of image processing and pattern recognition.     

Using adaptive and intelligent methods in constructing of a model of seismic noise

In the paper, an attempt is made to develop an approach to analysis of seismic signals with the use of Data Mining techniques. A system for registering of signals of seismic noise is described. Algorithms for signal segmentation are proposed. Geppener Vladimir Vladimirovich. Born 1940. Graduated from the Leningrad Electrotechnical Institute in 1964. Received candidate’s degree (in Engineering) in 1969 and Doctoral degree (in Engineering) in 2000. Professor at the Chair of Mathematical Software and Computer Applications of the St. Petersburg Electrotechnical University. Scientific interests: systems of signal processing, methods of artificial intelligence, and pattern recognition theory. Author and coauthor of more than 150 scientific publications. Member of the Russian Association for Pattern Recognition and Image Analysis. Tristanov Aleksandr Borisovich. Born 1981. Graduated with honors from the Kamchatka State Technical University in 2003. Post-graduate student at the Kamchatka State Pedagogical University. Works as an Assistant Professor at the Kamchatka State Pedagogical University. Scientific interests: systems of digital signal processing, methods of artificial intelligence, and frequency-time analysis of signals. Author of 10 scientific publications. Firstov Pavel Pavlovich. Born 1941. Graduated with honors from Polzunov Altai State Polytechnical Institute in 1963. Candidate of Sciences in Physics and Mathematics. Since 1965 works at the Institute of Volcanology and Seismology of the Far East Division of the Russian Academy of Sciences; Head of a laboratory. Scientific interest: volcanic acoustics, nature of earthquake predecessors. Author and coauthor of more than 100 papers and one monograph. Rulenko Oleg Petrovich. Born 1946. Graduated with honors from the Department of Physics and Mathematics of the Kamchatka State Pedagogical Institute in 1968. Received candidate’s degree (in Physics and Mathematics) in 1994. Senior Researcher at the Institute of Volcanology and Seismology of the Far East Division of the Russian Academy of Sciences. Scientific interests: atmospheric electricity, interaction of lithosphere and atmosphere, physics of earthquake predecessors. Author of 29 scientific publications.     

Partial evaluation technique for distributed image processing

In this paper, a partial evaluation technique to reduce communication costs of distributed image processing is presented. It combines application of incomplete structures and partial evaluation together with classical program optimization such as constant-propagation, loop unrolling and dead-code elimination. Through a detailed performance analysis, we establish conditions under which the technique is beneficial. Andrei Tchernykh received his Ph.D. degree in computer science from the Institute of Precise Mechanics and Computer Technology of the Russian Academy of Sciences (RAS), Russia in 1986. From 1975 to 1995 he was with the Institute of Precise Mechanics and Computer Technology of the RAS, Scientific Computer Center of the RAS, and at Institute for High Performance Computer Systems of the RAS, Moscow, Russia. Since 1995 he has been working at Computer Science Department at the CICESE Research Center, Ensenada, Baja California, Mexico. His main interests include cluster and Grid computing, incomplete information processing, and on-line scheduling. Vitaly Kober obtained his MS degree in Applied Mathematics from the Air-Space University of Samara (Russia) in 1984, and his PhD degree in 1992 and Doctoral degree in 2004 in Image Processing from the Institute of Information Transmission Problems, Russian Academy of Sciences. Now he is a titular researcher at the Centro de Investigation Cientifica y de Educatión Superior de Ensenada (Cicese), México. His research interests include signal and image processing, pattern recognition. Alfredo Cristóbal-Salas received his Ph.D. degree in computer science from the Computer Science Department at the CICESE Research Center, Ensenada, Baja California, México. Now he is a researcher at School of Chemistry Sciences and Engineering, University of Baja California, Tijuana, B.C. Mexico His main interests include cluster and Grid computing, incomplete information processing, and online scheduling. Iosif A. Ovseevich graduated from the Moscow Electrotechnical Institute of Telecommunications. Received candidate’s degree in 1953 and doctoral degree in information theory in 1972. At present he is Emeritus Professor at the Institute of Information Transmission Problems of the Russian Academy of Sciences. His research interests include information theory, signal processing, and expert systems. He is a Member of IEEE, Popov Radio Society.     

Clustering of signal components within most likely ECG episodes to analyze the ECG-waves

A computational cardiology based approach to find the number of ECG-waves responsible for generation and presentation of an ECG episode is proposed. The methodology adopted here is based on the comparison and study of diagnostic efficiency calculated from 12 lead ECG data. The diagnostic-efficiency is measured by using NN classifier whereas clustered points of most likely ECG-episode constitute the diagnostic feature. The result is also cross-validated using episodes transformed by existing signal transform technique, “Discrete Fourier Transform” and another transformation. “Velocity-Wave number Transform.” The result indicates the possible number of episode-clusters giving maximum diagnostic efficiency and also gives a new insight on ECG waves. The article is published in the original. Tapobrata Lahiri. Born in 1966. Graduated from Kalyani University, India in 1989. Received his PhD degree in Bio-physics in 1998. Assistant Professor at Indian Institute of Information Technology, Allahabad, India. Author of more than 25 publications. Scientific interests: Pattern Recognition. Systems Modelling and Simulation, Operation Research, Fractal and Chaos Analysis, Medical Informatics. Bioinformatics. Subrata Sarkar. Born in 1983. Received BE (Electronics and Communication) degree from Burdwan University, India in 2005. Doing his PhD in Engineering from Jadavpur University, Kolkata. Junior Research Fellow in DST, India sponsored ILTP Indo-Russian project. Scientific interests: Medical signal processing, Medical image processing. Aleksei Morozov. Born in 1968. Graduated from Bauman State Technical University, Moscow, in 1991. Received his PhD (Kandidat Nauk) degree in Physics and Mathematics in 1998. Senior Researcher at the Institute of Radio Engineering and Electronics of the Russian Academy of Sciences. Author of more than 60 publications. Scientific interests: biomedical signals analysis, logic programming, Internet agents. Sudip Sanyal. Born in 1957. Graduated from Banaras Hindu University, Varanasi, India in 1980. Received his PhD degree in Theoretical Nuclear Physics in 1986. Associate Professor at Indian Institute of Information technology, Allahabad, India. Author of more than 90 publications. Scientific interests: Pattern recognition, Information retrieval. Yurii Obukhov. Born in 1960. Graduated from the Moscow Institute of Physics and Technology in 1974. Obtained his Doctoral (Doctor Nauk) degree in Physics and Mathematics in 1992. Head of the Laboratory of the Institute of Radio Engineering and Electronics of the Russian Academy of Sciences. Current research interests: data visualizing, image analysis and processing, biomedical information science, and information systems. Author of more than 70 publications. Member of Editors Board of Biomedical Radioelectronics journal     

Stochastic filtering of approximate symmetries in dense packings of clusters

Certain questions concerning the arrangement of optimal dense packings of clusters are considered when simple routine long-term procedures are applied instead of a laborious method of direct solution. A unified approach to searching for hidden symmetries in such packings is proposed that represents a certain combination of the generalized Hough transform and the Purzen windows technique in nonparametric density estimation. All symmetries are sought via the Hough transforms adjusted to certain types of adjacent classes on the SO _N group manifold. Exact symmetries and separate solutions are filtered out by using the ergodic properties of the independent sequential choice procedure. Aleksandr Petrovich Vinogradov. Born 1951. Graduated from the Moscow Institute of Physics and Technology in 1974. Received candidates degree in physics and mathematics in the field of mathematical cybernetics. Scientific interests: pattern recognition, image analysis, application of algebraic and geometric methods to the problems of data analysis. Author of 45 papers. Jan Voracek (1962), graduated from Brno University of Technology (BUT) in 1985. Obtained his MS in Technical Cybernetics in 1985, first PhD in Technical Cybernetics in 1992, and second PhD in Manufacturing Technology in 1996, all from BUT. Since 1997 he has been working as a professor of information technology at the Laboratory of Information Processing, Lappeenranta University of Technology, Finland. Author and coauthor of more than 80 publications. Research interests include pattern recognition, image processing, and international education. Yuri I. Zhuravlev. Born 1935. Graduated from the Faculty of Mechanics and Mathematics, Moscow State University, in 1957. Received his PhD (Kandidat Nauk) degree in 1959 and Doctoral (Doktor Nauk) degree in Physics and Mathematics in 1965. Since 1969, with the Computer Center of the Russian Academy of Sciences, Moscow, first as a Laboratory Head and then as a Deputy Director. Professor at Moscow State University. Full member of the Russian Academy of Sciences (since 1992) and of the Academy of Sciences of Spain (since 1993). Scientific interests: mathematical logic; algebra; discrete optimization; pattern recognition; and the use of mathematical and computational methods for solving applied problems of data processing and research automation in industry, medicine, geology, and sociology. Author of more than 170 publications on information technology and applied mathematics. Editor-in-Chief of the journal Pattern Recognition and Image Analysis and a member of the editorial boards of several international and Russian journals on information technology and applied mathematics.