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.     

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.     

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.     

Preparing a common raster coverage for a territory based on hierarchical compressed presentation of orthoimages

Technology for the quick viewing of georeferenced images has been developed. Principles of the organization and structure of hierarchical HGI format, which is intended to store compressed images with controlled maximal error, are presented. Additionally, a basic method of HGI format compression is described. The advantages of using the HGI format for covering a territory with orthoimages are described. Mikhail Valer’evich Gashnikov. Born in 1975. Graduated from Samara State Aerospace University (SGAU) in 1998. Received Candidate’s degree in 2002 in technical sciences. Associate Professor at the Department of Geoinformatics, Samara State Aerospace University. Scientific interests include image processing, compression of images, and statistical coding. He is the author of 50 scientific publications, including 21 articles and one monograph (as a coauthor). He is a member of the Russian Association for Pattern Recognition and Image Analysis. Nikolai Ivanovich Glumov. Born in 1962. Graduated from Kuibyshev State Aeronautical Institute (currently Samara State Aerospace University) in 1985. Received his Candidate’s degree in 1994 in technical sciences and currently works as a Senior Research Associate at the Image Processing Systems Institute of the Russian Academy of Science. Scientific interests include processing remote sensing data and image recognition, image compression, the formation of modeling systems of digital images. He is the author of more than 90 scientific publications, including 30 articles and one monograph (as a coauthor). He is a member of the Russian Association for Pattern Recognition and Image Analysis. Andrei Vladimirovich Chernov. Born in 1975. Graduated from Samara State Aerospace University in 1998. Received Candidate’s degree in 2004 in technical sciences and currently works as an Associate Professor at the Department of Geoinformatics, Samara State Aerospace University. Scientific interests include processing remote sensing data and image recognition. He is the author of more then 50 scientific publications, including 24 articles and one monograph (as a co-author). He is a member of the Russian Association for Pattern Recognition and Image Analysis.     

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.     

Color correction of vehicle images during the sequential registration of color channels

An algorithm for the image normalization of moving objects during the sequential registration of color RGB channels has been developed. This algorithm allows many-colored moving objects to be joined and their characteristics to be calculated; it is based on the use of intercommunication between the coordinates, sizes, and orientations of many-colored copies of objects. Mikhail Valer’evich Gashnikov. Born in 1975. Graduated from Samara State Aerospace University (SGAU) in 1998. Received Candidate’s degree in 2002 in technical sciences. Associate Professor at the Department of Geoinformatics, Samara State Aerospace University. Scientific interests include image processing, compression of images, and statistical coding. He is the author of 50 scientific publications, including 21 articles and one monograph (as a coauthor). Member of the Russian Association for Pattern Recognition and Image Analysis. Andrei Vladimirovich Chernov. Born in 1975. Graduated from Samara State Aerospace University (SGAU) in 1998. Received Candidate’s degree in 2004 in technical sciences. Associate Professor at the Department of Geoinformatics, Samara State Aerospace University. Scientific interests include the processing of remote sensing data and image recognition. He is the author of more than 50 scientific publications, including 24 articles and one monograph (as a coauthor). Member of the Russian Association for Pattern Recognition and Image Analysis. Nikolai Viktorovich Chupshev. Born in 1986. Graduated from Samara State Aerospace University (SGAU) in 2008. Scientific interests include image processing and recognition and geoinformatic systems. Has three publications, including one article.     

Recognizing rectangular objects in digitized topographic maps

An object-oriented approach to unsupervised vectorization of rectangular objects in topographic maps based on their recognition by geometric features is presented. An implementation of this approach led to a two- to threefold reduction in labor needed to develop vector models of buildings and industrial installations from their maps. Andrei V. Chernov. Born 1975. Graduated from the Samara State Aerospace University (SSAU) in 1998. In 2004 defended a Candidate dissertation (Eng.). Currently a senior lecturer at the Chair of Geoinformation Systems, SSAU.Scientific interests: geographical information systems, processing of remote sensing data, and pattern recognition. Author of more than 50 publications, including 24 papers in scientific journals, and a co-author of a monograph. Member of the Russian Federation Association of Pattern Recognition and Image Analysis. Nikolai V. Chupshev. Born 1986. Graduated from the Samara State Aerospace University (SSAU) in 2008. Scientific interests: image analysis, geographical information systems, and pattern recognition. Author of three publications including one journal paper.     

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.     

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.     

Efficiency analysis of image compression algorithms based on hierarchical and wavelet representations

The efficiency of hierarchical and wavelet image compression methods is analyzed and compared. More specifically, hierarchical grid interpolation (HGI) is compared with JPEG-2000. The characteristics of both methods are analyzed, and recommendations are given concerning their use in various image-processing applications. Alina Yur’evna Bavrina. Born 1980. Graduated from the Samara State Aerospace University in 2003. Received her candidate’s degree in technical sciences in 2006. Junior researcher at the Image Processing Systems Institute of the Russian Academy of Sciences. Research interests: image processing, image compression, and geoinformation technology. Author of more than 20 publications, including 6 papers. Member of the Russian Association for Pattern Recognition and Image Analysis. Mikhail Valer’evich Gashnikov. Born 1975. Graduated from the Samara State Aerospace University (SSAU) in 1998. Received his candidate’s degree in technical sciences in 2002. Associate professor at the SSAU Department of Geoinformatics. Research interests: image processing, compression, and statistical coding. Author of more than 50 publications, including 21 papers and 1 monograph (coauthored). Member of the Russian Association for Pattern Recognition and Image Analysis. Nikolai Ivanovich Glumov. Born 1962. Graduated from the Kuibyshev Aviation Institute (now the Samara State Aerospace University) in 1985. Received candidate’s degree in technical sciences in 1994. Senior researcher at the Image Processing Systems Institute of the Russian Academy of Sciences. Research interests: image processing, pattern recognition, image compression, and simulation of digital image formation systems. Author of more than 90 publications, including more than 30 papers and 1 monograph (coauthored). Member of the Russian Association for Pattern Recognition and Image Analysis.     

Analysis of semantic relations in classification of sense images of statements

Semantic relations in classification of images of natural-language statements are analyzed. The classification of the sense images of statements is considered on an example of construction of semantic relations in the RussNet thesaurus. The semantic statements are formalized with mathematical methods of the lattice theory. Gennadii M. Emel’yanov. Born 1943. Graduated from Leningrad Institute of Electrical Engineering in 1966. Received candidate’s degree in 1971 and doctoral degree in 1990. Head of the Department of Computer Software for Computer Devices and Computerized Systems at Novgorod State University. Scientific interests: construction of problem-oriented computer systems for image processing and analysis. Dmitrii V. Mikhailov. Born 1974. Graduated from Novgorod State University in 1997. Received candidate’s degree in 2003. Staff member of the Department of Computer Software for Computer Devices and Computerized Systems at Novgorod State Unniversity. Member of the Russian Association of Pattern Recognition and Image Analysis since 2002. Scientific interests: computer linguistics and artificial intelligence. Author of 15 papers. Nadezhda A. Stepanova. Born 1979. Graduated from Novgorod State University in 2001. PhD Student at Novgorod State University. Scientific interests: computer linguistics, semantics, lattice theory, intensional logic.     

Filling in the government-pattern dictionary in the analysis of equivalence for sense images of statements

Automatic filling in a language knowledgebase in analysis of the sense equivalence of statements is considered in the framework of an original approach based on a theory that represents language as a sense-to-text converter. Gennadii M. Emel’yanov. Born 1943. Graduated from Leningrad Institute of Electrical Engineering in 1966. Received candidate’s degree in 1971 and doctoral degree in 1990. Head of the Department of Computer Software for Computer Devices and Computerized Systems at Novgorod State University. Scientific interests: construction of problem-oriented computer systems for image processing and analysis. Dmitrii V. Mikhailov. Born 1974. Graduated from Novgorod State University in 1997. Received candidate’s degree in 2003. Staff member of the Department of Computer Software for Computer Devices and Computerized Systems at Novgorod State Unniversity. Member of the Russian Association of Pattern Recognition and Image Analysis since 2002. Scientific interests: computer linguistics and artificial intelligence. Author of 15 papers.     

Method for the automatic georeferencing and calibration of cartographic images

The paper considers one of the stages of creating and reneqing digital maps, i.e., georeferencing and calibrating cartographic representations (scanned topographic drawings). It is proposed to use the standards accepted in Russia for paper maps to search for intersections in the coordinate lines using known physical coordinates. An algorithmic system and software consisting of the following stages have been developed: search for interior and exterior margins of the topographic drawing, search for intersections of coordinate lines, verification of detected control points, and geometric transformation. The use of this method allows one to exclude hand labor by operators, which saves 10–20 min per map board. Ol’ga Aleksandrova Titova. Born in 1980. Graduated from Samara State Aerospace University (SGAU) in 2003. Received Candidate’s degree in 2006 in technical sciences. An assistant at the Geoinformatics Department of SGAU and a trainee observer at the Image Processing Systems Institute of Russian Academy of Science. Scientific interests include digital signal and image processing, including remotesensing data, geoinformation systems, and image recognition. She is the author of 19 scientific publications, including four articles, and a Member of the Russian Association for Pattern Recognition and Image Analysis. Andrei Vladimirovich Chernov. Born in 1975. Graduated from Samara State Aerospace University (SGAU) in 1998. Received Candidate’s degree in 2004 in technical sciences. Associate Professor at the Department of Geoinformatics, Samara State Aerospace University. Scientific interests include processing remote sensing data and image recognition. He is the author of more than 50 scientific publications, including 24 articles and one monograph (as a coauthor), as well as a member of the Russian Association for Pattern Recognition and Image Analysis.     

Comparison of the efficiencies of image compression algorithms based on separable and nonseparable two-dimensional Haar wavelet bases

Compression algorithms for digital images are described that are based on nonseparable two-dimensional wavelet transforms on nonrectangular supports. The efficiencies of these algorithms are experimentally investigated and compared with those of a compression algorithm based on a separable Haar wavelet basis. Aleksandr Mikhailovich Belov. Born 1980. Graduated from the Samara State Aerospace University. Received candidate’s degree in physics and mathematics in 2007. Currently is a junior scientist at the Institute of Image Processing, Russian Academy of Sciences. Scientific interests: discrete orthogonal transforms, fast algorithms for discrete orthogonal transforms, and the theory of canonical number systems. Author of 20 publications, including 8 papers. Member of the Russian Pattern Recognition and Image Processing Association.     

Fast algorithm for recursive computation of the convolution of an image with a two-dimensional inseparable polynomial FIR filter

A method for constructing an algorithm for recursive computation of the convolution of an image with a two-dimensional polynomial FIR filter is proposed. It is important to note that the filter is not decomposed into separable functions. The algorithm is compared to the known procedure based on such a decomposition, and its computational complexity is estimated via analytic expressions. Vladislav Valer’evich Myasnikov. Born 1971. Graduated from the Samara State Aerospace University (SSAU) in 1994. Received candidate’s degree (in Engineering) in 1998. Senior Researcher at the Institute of Systems for Image Processing, the Russian Academy of Sciences, and Assoc. Prof. at the Chair of Geoinformatics of the SSAU. Scientific interests: digital signal and image processing, geoinformatics, neuron networks, pattern recognition. Author of about 60 publications, including 24 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis.     

Clusterization of semantic meanings in the problem of sense equivalence situation recognition

A complex approach to the formalization of sense relations between lexeme and its lexical correlates as precedents of the sense equivalence situations is presented. A technique is outlined for the presentation and usage of information on the lexical meaning of a natural language word to solve the problem of pattern recognition based on standard lexical functions. Dmitriy V. Mikhailov. Born 1974. Graduated from the Yaroslav-the-Wise Novgorod State University, Novgorod, in 1997. From 1997 to 2000, a computer engineer at the Staroruspribor plant in Staraya Russa, Novgorod region. Obtained his PhD (Kandidat Nauk) degree in Physics and Mathematics in 2003. From 2000 to 2007 has worked at the Department of Computer Software of Novgorod State University. Now he is a Docent of the Department of Information Technologies and Systems at the same university. Since 2002 is a member of Russian Association for Pattern Recognition and Image Analysis. Scientific interests: computational linguistics and artificial intelligence. In scientific area of Pattern Recognition and Image Analysis has 18 papers. Gennadii M. Emelyanov. Born 1943. Graduated from the Leningrad Institute of Electrical Engineering in 1966. Obtained his PhD (Kandidat Nauk) and his Doctoral (Doktor Nauk) degrees in 1971 and 1990, respectively. From 1993 to 2003, a Dean of the Faculty of Mathematics and Computer Science at Yaroslavthe-Wise Novgorod State University. Now he is a Professor of the Department of Information Technologies and Systems at the same university. Scientific interests: construction of problem-oriented computing systems of image processing and analysis.     

Methods of recognition based on the function of rival similarity

A unified approach to the development of pattern recognition methods is proposed. The approach is based on the employment of the function of rival similarity (FRiS-function), which adequately represents human methods of evaluation of similarity and difference. Methods of recognition based on this approach are briefly described. Examples of solution of actual and benchmark problems using FRiS-function are given. Nikolai Grigor’evich Zagoruiko finished a secondary school in Novosibirsk oblast. Graduated from the Electroengineering Department of the Leningrad Institute of Motion-picture Engineers in 1953. Since 1960 has been working at the Institute of Mathematics of the Siberian Branch of the Russian Academy of Sciences. Received candidate’s degree in 1962 and doctoral degree in Pattern Recognition in 1969. Since 1973 to 1982 had been working as a vice-rector of the Novosibirsk State University. In 1988–1990 had been heading a project in the International Laboratory of Artificial Intelligence in Bratislava (Slovakia). Scientific interests: pattern recognition and prediction. Author of 219 publications, including 13 monographs. Vladimir Vladimirovich Dyubanov. Born 1981. Graduated from the Krasnoyarsk State University in 2002. Currently is a postgraduate at the Novosibirsk State University. Scientific interests: data mining and pattern recognition and prognosis. Author of eight papers. Ol’ga Andreevna Kutnenko. Born 1958. Graduated from the Novosibirsk State University in 1980. Received candidate’s degree in 2000. Scientific interests: data analysis, determination of empirical principles, pattern recognition. Author of 13 papers. Irina Artemovna Borisova. Born 1978. Graduated from the Novosibirsk State University in 2002. Currently is a chief programmer at the Institute of Mathematics, Siberian Division, Russian Academy of Sciences. Scientific interests: pattern recognition. Author of nine papers.     

Efficient convolution algorithms with an FIR representable as a spline

The convolution is calculated in the case when the finite impulse response can (FIR) be representable as a spline. This approach is a practical illustration of the method proposed in [4, 5] for constricting an efficient convolution algorithm. A brief theoretical justification of the approach is given. An efficient convolution algorithm for a Gaussian FIR is constructed as an example and is compared with other convolution algorithms. Vladislav Valer’evich Myasnikov. Born 1971. Graduated from the Samara State Aerospace University (SSAU) in 1994. Began his graduate study at SSAU in 1995 and received candidate’s degree in technical sciences in 1998. Senior researcher at the Image Processing Systems Institute of the Russian Academy of Sciences and associate professor at the SSAU Department of Geoinformatics. Research interests: digital signal and image processing, geoinformatics, neural networks, and pattern recognition. Author of more than 60 publications, including 24 papers and 1 monograph (coauthored). Member of the Russian Association for Pattern Recognition and Image Analysis. Ol’ga Aleksandrovna Titova. Born 1980. Graduated with honors from the Samara State Aerospace University in 2003. Graduate student at SSAU from 2003 to 2006. Assistant professor at the SSAU Department of Geoinformatics. Research interests: digital processing of signals and images, including remote sensing data; geoinformation systems; and pattern recognition. Author of 19 publications, including 4 papers. Member of the Russian Association for Pattern Recognition and Image Analysis.     

Efficiency of the reduced wise algorithm over a set of convolution algorithms

A reduction operation and the design of a reduced wise algorithm over a set of known algorithms of unvarying complexity are addressed. A direct convolution algorithm and the best-known algorithms based on fast discrete orthogonal transforms (with Cooley-Tukey and Good-Thomas decompositions and the Rader algorithm for short lengths) are used as a support set of known algorithms. It is shown that their combined use in the reduced wise algorithm decreases the computational complexity of the resulting convolution algorithm as compared to that of the algorithms in the support set. Alina Yur’evna Bavrina. Born 1980. Graduated from the Samara State Aerospace University in 2003. Received candidate’s degree in technical sciences in 2006. Junior researcher at the Image Processing Systems Institute of the Russian Academy of Sciences. Research interests: image processing, image compression, and geoinformation technology. Author of more than 20 publications, including 6 papers. Member of the Russian Association for Pattern Recognition and Image Analysis. Vladislav Valer’evich Myasnikov. Born 1971. Graduated from the Samara State Aerospace University (SSAU) in 1994. Started his graduate study at SSAU in 1995 and received candidate’s degree in technical sciences in 1998. Senior researcher at the Image Processing Systems Institute of the Russian Academy of Sciences and associate professor at the SSAU Department of Geoinformatics. Research interests: digital signal and image processing, geoinformatics, neural networks, and pattern recognition. Author of more than 60 publications, including 24 papers and 1 monograph (coauthored). Member of the Russian Association for Pattern Recognition and Image Analysis.