A two-step approach for automatic microscopic image segmentation using fuzzy clustering and neural discrimination

The early diagnosis of lymphatic system tumors heavily relies on the computerized morphological analysis of blood cells in microscopic specimen images. Automating this analysis necessarily requires an accurate segmentation of the cells themselves. In this paper, we propose a robust method for the automatic segmentation of microscopic images. Cell segmentation is achieved following a coarse-to-fine approach, which primarily consists in the rough identification of the blood cell and, then, in the refinement of the nucleus contours by means of a neural model. The method proposed has been applied to different case studies, revealing its actual feasibility. This article was submitted by the authors in English. Sara Colantonio, M. Sc. honors degree in Computer Science from the University of Pisa in 2004, PhD student in Information Engineering at the Dept. of Information Engineering, Pisa University, is a research fellow at the Institute of Information Science and Technologies of the Italian National Research Council, in Pisa. She has a grant from Finmeccanica for studies in the field of image categorization with applications in medicine and quality control. Her main interests include neural networks, machine learning, industrial diagnostics, and medical imaging. She is a coauthor of more than fifteen scientific papers. At present, she is involved in a number of European research projects regarding image mining, information technology, and medical decision support systems. Ovidio Salvetti, director of research at the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council (CNR), in Pisa, is working in the field of theoretical and applied computer vision. His fields of research are image analysis and understanding, pictorial information systems, spatial modeling, and intelligent processes in computer vision. He is a coauthor of four books and monographs and more than three hundred technical and scientific articles; he also possesses ten patents regarding systems and software tools for image processing. He has been a scientific coordinator of several national and European research and industrial projects, in collaboration with Italian and foreign research groups, in the fields of computer vision and high-performance computing for diagnostic imaging. He is member of the editorial boards of the international journals Pattern Recognition and Image Analysis and G. Ronchi Foundation Acts. He is at present the CNR contact person in ERCIM (the European Research Consortium for Informatics and Mathematics) for the Working Group on Vision and Image Understanding, member of IEEE and of the steering committee of a number of EU projects. He is head of the ISTI Signals and Images Laboratory. Igor B. Gurevich. Born 1938. Dr. Eng. [Diploma Engineer (Automatic Control and Electrical Engineering), 1961, Moscow Power Engineering Institute, Moscow, USSR]; Dr. (Theoretical Computer Science/Mathematical Cybernetics), 1975, Moscow Institute of Physics and Technology, Moscow, USSR. Head of department at the Dorodnicyn Computing Center of the Russian Academy of Sciences, Moscow; assistant professor at the Computer Science Faculty, Moscow State University. He has worked from 1960 to present as an engineer and researcher in industry, medicine, and universities and in the Russian Academy of Sciences. Area of expertise: image analysis, image understanding, mathematical theory of pattern recognition, theoretical computer science, pattern recognition and image analysis techniques for applications in medicine, nondestructive testing, process control, knowledge bases, knowledge-based systems. Two monographs (in coauthorship), 135 papers on pattern recognition, image analysis, theoretical computer science and applications in peer reviewed international and Russian journals, conference and workshop proceedings; one patent of the USSR, four patents of the RF Executive Secretary of the Russian Federation Association for Pattern Recognition and Image Analysis, member of the International Association for Pattern Recognition Governing Board (representative from the Russian Federation), IAPR fellow. He has been the PI of many research and development projects as part of national research (applied and basic research) programs of the Russian Academy of Sciences, of the Ministry of Education and Science of the Russian Federation, of the Russian Foundation for Basic Research, of the Soros Foundation, and of INTAS. Vice Editor-in-Chief of Pattern Recognition and Image Analysis, International Academic Publishing Company “Nauka/Interperiodica” Pleiades Publishing.     

Cell image analysis ontology

Cell image analysis in microscopy is the core activity of cytology and cytopathology for assessing cell physiological (cellular structure and function) and pathological properties. Biologists usually make evaluations by visually and qualitatively inspecting microscopic images: this way, they are particularly able to recognize deviations from normality. Nevertheless, automated analysis is strongly preferable for obtaining objective, quantitative, detailed, and reproducible measurements, i.e., features, of cells. Yet, the organization and standardization of the wide domain of features used in cytometry is still a matter of challenging research. In this paper, we present the Cell Image Analysis Ontology (CIAO), which we are developing for structuring the cell image features domain. CIAO is a structured ontology that relates different cell parts or whole cells, microscopic images, and cytometric features. Such an ontology has incalculable value since it could be used for standardizing cell image analysis terminology and features definition. It could also be suitably integrated into the development of tools for supporting biologists and clinicians in their analysis processes and for implementing automated diagnostic systems. Thus, we also present a tool developed for using CIAO in the diagnosis of hematopoietic diseases. The text was submitted by the authors in English. Sara Colantonio. MSc degree with honors in computer science, University of Pisa, 2004; PhD student in information engineering at the Department of Information Engineering, Pisa University; research fellow at the Institute of Information Science and Technologies, National Research Council, Pisa. Received a grant from Finmeccanica for studies in the field of image categorization with applications in medicine and quality control. Her main interests include neural networks, machine learning, industrial diagnostics, and medical imaging. Coauthor of more than 30 scientific papers. Currently involved in a number of European research projects regarding image mining, information technology, and medical decision support systems. Igor B. Gurevich. Born 1938. Dr. Eng. (Diploma Engineer (Automatic Control and Electrical Engineering), 1961, Moscow Power Engineering Institute, Moscow, USSR); Dr. (Theoretical Computer Science/Mathematical Cybernetics), 1975, Moscow Institute of Physics and Technology, Moscow, USSR. Head of department at the Dorodnicyn Computing Center of the Russian Academy of Sciences, Moscow; assistant professor at the Faculty of Computer Science, Moscow State University. Since 1960, has worked as an engineer and researcher in industry, medicine, and universities and in the Russian Academy of Sciences. Area of expertise: image analysis; image understanding; mathematical theory of pattern recognition; theoretical computer science; pattern recognition and image analysis techniques for applications in medicine, nondestructive testing, and process control; knowledge bases; knowledge-based systems. Two monographs (in coauthorship); 135 papers on pattern recognition, image analysis, and theoretical computer science and applications in peer-reviewed international and Russian journals and conference and workshop proceedings; one patent of the USSR and four patents of the RF. Executive secretary of the Russian Association for Pattern Recognition and Image Analysis, member of the governing board of the International Association for Pattern Recognition (representative from the Russian Federation), IAPR fellow. Has served as PI of many research and development projects as part of national research (applied and basic) programs of the Russian Academy of Sciences, the Ministry of Education and Science of the Russian Federation, the Russian Foundation for Basic Research, the Soros Foundation, and INTAS. Deputy editor in chief of Pattern Recognition and Image Analysis. Massimo Martinelli. Works at the Institute of Information Science and Technologies (ISTI), National Research Council (CNR), Pisa. Member of the W3C multimedia semantics incubator group; coordinator of the CNR-ISTI web systems group. His main interests include semantic web and web technologies. Coauthor of more than 50 scientific papers. Currently involved in a number of European research projects regarding semantic web, information technology, multimedia semantics, and medical decision support systems. Ovidio Salvetti. Director of research at the Institute of Information Science and Technologies (ISTI), National Research Council (CNR), Pisa. Working in the field of theoretical and applied computer vision. His fields of research are image analysis and understanding, pictorial information systems, spatial modeling, and intelligent processes in computer vision. Coauthor of four books and monographs and more than 300 technical and scientific articles, with ten patents regarding systems and software tools for image processing. Has served as a scientific coordinator of several national and European research and industrial projects, in collaboration with Italian and foreign research groups, in the fields of computer vision and high-performance computing for diagnostic imaging. Member of the editorial boards of the international journals Pattern Recognition and Image Analysis and G. Ronchi Foundation Acts. Currently the CNR contact person in ERCIM (the European Research Consortium for Informatics and Mathematics) for the Working Group on Vision and Image Understanding and a member of IEEE and of the steering committee of a number of EU projects. Head of the ISTI Signals and Images Laboratory. Yulia O. Trusova. Born 1980. Graduated from the Faculty of Computational Mathematics and Cybernetics of Lomonosov Moscow State University in 2002. Works at the Dorodnicyn Computing Center of the Russian Academy of Sciences. Scientific interests: mathematical theory of pattern recognition and image analysis, methods of discrete mathematics, databases and knowledge bases, and computational linguistics. Coauthor of more than 25 papers. Laureate of the Aspirant Award, 2003–2005. Member of the Russian 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.     

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.     

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.     

On the uni- and bimodality of a two-component Gaussian mixture

Several sufficient conditions are formulated for the uni- and bimodality of a mixture of two Gaussian distributions with equal variances σ² and different expectation values μ _i , i = 1, 2. An equation governing all the degenerate critical inflection points for the probability density f(x) of the mixture is derived by a statistical method. This equation describes the boundary of the uni- and bimodality domains of f(x). Nina Nikolaevna Aprausheva was born in 1940. Graduated from the Moscow State University (Department of Mechanics and Mathematics) in 1966. In 1982, defended the Cand. Sci. thesis “On the Application of Mixtures of Normal Distributions in Pattern Recognition.” Senior scientist at Dorodnicyn Computing Center, Russian Academy of Sciences. Scientific interests: mathematical statistics, computational mathematics, mathematical methods in pattern recognition, and decision theory (about 75 publications). Member of Association of Pattern Recognition and Association of. “Women in science and education.” N.N. Aprausheva’s publications have been awarded several prizes at the scientific publications contests in Computing Center of Russian Academy of Sciences. Stanislav Viktorovich Sorokin was born in 1947. Graduated from Moscow State University (Department of Computational Mathematics and Cybernetics) in 1971. Programmer at Dorodnicyn Computing Center, Russian Academy of Sciences. Scientific interests: computational mathematics, system programming, and pattern recognition (20 publications).     

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.     

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.     

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.     

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.     

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.     

Bounds for the number of modes of the simplest Gaussian mixture

Several theorems on sufficient unimodality conditions are formulated for a sum of k normal distributions with the same variance and with different mean values μ _i , i = 1, ..., k, 2 ≤ k < ∞, taken with their a priori probabilities π_i. On the basis of these theorems, estimates for the lower and upper bounds for the mode numbers m are obtained for k ≥ 3 in the case when the mixture contains k* components, 2 ≤ k* < k, satisfying the unimodality conditions. Aprausheva Nina Nikolaevna (b. 1940). Graduated from the Moscow State University (Department of Mechanics and Mathematics) in 1966. In 1982, defended the Cand. Sci. thesis “On the Application of Mixtures of Normal Distributions in Pattern Recognition.” Senior scientist at Dorodnicyn Computing Center, Russian Academy of Sciences. Scientific interests: mathematical statistics, computational mathematics, mathematical methods in pattern recognition, and decision theory (about 70 publications). Member of Association of Pattern Recognition. Mollaverdi Naser (b. 1967). Graduated from the Isfahan University of Technology (Iran) in 1990. In 1995, graduated from the Educational University (Teheran, Iran). Third-year scholar at Moscow State University (Department of Computational Mathematics and Cybernetics). Scientific interests: computational mathematics, pattern recognition, programming, and statistics (12 publications). Sorokin Stanislav Viktorovich (b. 1947). Graduated from Moscow State University (Department of Computational Mathematics and Cybernetics) in 1971. Programmer at Dorodnicyn Computing Center, Russian Academy of Sciences. Scientific interests: computational mathematics, system programming, and pattern recognition (15 publications).     

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.     

Wiener estimation method in estimating of spectral reflectance from RGB images

Color is one of the most important features in digital images. The representation of color in digital form with a three-component image (RGB) is not very accurate, hence the use of a multiple-component spectral image is justified. At the moment, acquiring a spectral image is not as easy and as fast as acquiring a conventional three-component image. One answer to this problem is to use a regular digital RGB camera and estimate its RGB image into a spectral image by the Wiener estimation method, which is based on the use of a priori knowledge. In this paper, the Wiener estimation method is used to estimate the spectra of icons. The experimental results of the spectral estimation are presented. The text was submitted by the authors in English. Pekka Tapani Stigell. Year of birth 1976. Year of graduation and name of institution: Last year undergraduate student in the Department of Computer Science in the University of Joensuu, Finland. Affiliation: InFotoics Center, Department of Computer Science, University of Joensuu. Position: Trainee. Area of research: Color research. Number of publications: 1. Membership to scientific societies: Pattern Recognition Society of Finland, member-society of IAPR (International Association for Pattern Recognition). Prizes for achievements in research or applications: The best young scientist award in PRIA-7-2004 (shared with two other scientists). Kimiyoshi Miyata. Year of birth: 1966. Year of graduation and name of institution: 2000. Graduate School of Science and Technology, Chiba University, Japan. Year of graduation: 1990, BE degree (Chiba University), 1992, ME degree (Chiba University), 2000, Ph.D degree (Chiba University). Affiliation: Museum Science Division, Research Department, National Museum of Japanese History. Position: Assistant Professor. Area of research: Improvement of image quality, color management, application of imaging science and technology to museum activities. Number of publications: 11. Membership to scientific societies: Society of Photographic Science and Technology of Japan, Optical Society of Japan, Institute of Image Electronics Engineers of Japan, Society for Imaging Science and Technology. Prizes for achievements in research or applications: Progressing Award from Society of Photographic Science and Technology of Japan in 2000, Itek Award from Society for Imaging Science and Technology in 2000. Markku Hauta-Kasari. Year of birth: 1970. Graduation and name of the institution: University of Technology, Lappeenranta, Finland. Year of graduation: 1999, Ph.D. degree (University of Technology, Lappeenranta). Affiliation: InFotonics Center, Department of Computer Science, University of Joensuu. Position: Director. Area of research: Color research, neural computation, pattern recognition, optical pattern recognition, computer vision, image processing. Number of publications: Articles in refereed international scientific journals: 5, Articles in refereed international scientific conferences: 9, Other Scientific Publications: 40. Membership to academies: Chairman of the Pattern Recognition Society of Finland May 2003. Membership to scientific societies: Pattern Recognition Society of Finland, member-society of IAPR (International Association for Pattern Recognition), Finnish Information Processing Association, Finnish Union of University Researchers and Teachers, Optical Society of Japan, Optical Society of America. Prizes for achievements in research or applications: The best Ph.D.-thesis award in the field of pattern recognition in 1998–1999 in Finland. Award was issued by the Pattern Recognition Society of Finland on April 25, 2000.     

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.     

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.