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.     

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.     

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.     

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.     

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.     

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.     

Construction of an efficient algorithm over a set of linear convolution algorithms

An efficient algorithm for computing a linear convolution is constructed. It is proved that the construction can be represented as three consecutive operations. The first involves the construction of a wise algorithm over the set of convolution algorithms. The second is the construction of a reduced wise algorithm. The third is the construction of an induced algorithm chosen from an extension of the set consisting of a single reduced wise algorithm. Theorems are formulated that give necessary and sufficient conditions for the efficiency and strict efficiency of the algorithm constructed. 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, computer vision, pattern recognition, neural networks, and geoinformatics. Author of more than 60 publications, including 24 papers and 1 monograph (coauthored). Member of the Russian Association for Pattern Recognition and Image Analysis.     

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.     

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.     

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.     

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.     

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.     

Method for estimating lineature by scanned samples of documents

The paper considers an algorithm for estimating lineature of scanned digital images based on the calculation of series lengths and local directional fields. The results of an experiment are given and the efficiency of the algorithm is investigated. Vitalii Anatol’evich Mitekin. Born in 1983. Graduated from Samara State Aerospace University (SSAU) in 2006. At present, he is a post-graduate student in the Department of Geoinformatics at SSAU. His scientific interests include image processing, stenography, and cryptography. He is the author of three publications, including three articles. Viktor Andreevich Fedoseev. Born in 1986. Defended a degree thesis at the Samara State Aerospace University in 2007. Continues teaching at the SSAU at present, and also works as a technician at the Institute of Image Processing Systems at the Russian Academy of Sciences. His scientific interests include computer graphics, image processing, stenography, and cryptography. He is the author of 11 publications, including six articles.     

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.     

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 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.     

Investigation of methods of estimating geometrical misalignment in face images

Two methods of estimating the geometrical misalignment parameters for portrait images are considered in the work. The first method is based on use of the Fourier transform and application of the correlative approach and the second is based on calculating the moment characteristics of an image. Results of experimental studies are presented. The advantage of the method based on the Fourier transformation is shown. Recommendations for both methods are given. Evgenii Valer’evich Myasnikov. Born in 1981. Graduated from Samara State Aerospace University (SSAU) 2004. Completed his post-graduate studies at SSAU and received his candidate’s degree in 2007 (technical sciences). Myasnikov is currently with both the Institute of Image Processing RAS as a probationer-researcher and SSAU as a junior member of teaching at the geoinformatics chair. Scientific interests include the creation of software complexes, image processing and pattern recognition, and searching for images in databases. He is the author of 23 publications, including six articles, and a member of the Russian Association for 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.     

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.     

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.