Identification of stable description elements using an active sensor

A two-phase method for the pattern-driven recognition of objects in images is presented, implemented, and tested numerically. The method is based on the use of an active sensor. Possibilities for development are envisaged. This approach was shown to have advantages in solving the object-background separation problem and a high recognition rate was achieved with slow learning. Dmitrii I. Mednikov. Born in 1987. Fifth-year student at the Faculty of Mathematics and Mechanics of Moscow State University. Scientific interests include image recognition and image processing. Author of one paper. Alexei Milovidov. Born in 1986. Graduated from the Faculty of Mathematics and Mechanics of Moscow State University in 2008. Scientific interests include image recognition. Author of 3 papers. Semen Yu. Sergunin. Born in 1980. Graduated from the Faculty of Mathematics and Mechanics of Moscow State University in 2002. Postgraduate student at the same faculty. Scientific interests include image recognition. Author of five papers. Mikhail I. Kumskov. Born in 1956. Graduated from the Faculty of Computational Mathematics and Cybernetics of Moscow State University in 1978. Received his candidate’s degree in Physics and Mathematics in 1981 and doctoral degree in 1997. Professor at the Department of Computational Mathematics of the Faculty of Mathematics and Mechanics of Moscow State University. Scientific interests include the prediction of properties of chemical compounds, optimization of structural objects representation for classification problems, and image processing. Author of more than 50 papers.     

Computational model for recognition of scene objects with an active sensor

In the paper, a computational model for recognition of objects in a scene image is presented. The model is based on the use of an active sensor. The structure of the object model (OM) is described. This structure is a component that stores different representations of the object and puts at user’s disposal an interface whose operations are used in the scene recognition process. Semen Yu. Sergunin. Born 1980. Graduated from the Faculty of Mathematics and Mechanics of Moscow State University in 2002. Finished postgraduate course of the Department of Computational Mathematics of the same faculty. Scientific interests include image recognition. Author of about 20 papers. Mikhail I. Kumskov. Graduated from the Faculty of Computational Mathematics and Cybernetics of Moscow State University in 1978. Received his candidate’s degree (in Physics and Mathematics) in 1981 and doctoral degree in 1997. In 1981–1997 taught at the Faculty of Computational Mathematics and Cybernetics in the special seminar on Computer Graphics and Image Processing of the Department of Automation of Systems of Computational Complexes. Since 1992 works at the laboratory of Mathematical Chemistry of the Zelinsky Institute of Organic Chemistry of the Russian Academy of Sciences. Since 1997 teaches at the Department of Computational Mathematics of the Faculty of Mathematics and Mechanics of Moscow State University. Author of more than 50 papers. Scientific interests include prediction of properties of chemical compounds, optimization of structural object representation for classification problems, and image understanding.     

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.     

Image enhancement by total variation quasi-solution method

A new method of image restoration based on the quasi-solution method for a compact set of functions with bounded total variation is introduced. Application of this method does not require estimation of the noise level, which is necessary to choose the regularization parameter in the Tikhonov regularization method. The approbation of this method with test images shows its effectiveness for image deringing. The text was submitted by the authors in English. Andrey S. Krylov. Born 1956. Graduated from the Faculty of Computational Mathematics and Cybernetics, Moscow State University (MGU). Received the degree of PhD in 1983. Currently an associate professor and head of the Laboratory of Mathematical Methods of Image Processing at the Faculty of Computational Mathematics and Cybernetics, MGU. His main research interests lie in mathematical methods of multimedia data processing. Vladimir N. Tsibanov. Born 1982. Graduated from the Faculty of Computational Mathematics and Cybernetics, Moscow State University (MGU). He is currently a PhD student at the Faculty of Computational Mathematics and Cybernetics, MGU. His main research interests lie in variational methods in image processing. Alexander M. Denisov. Born 1946. Graduated from the Faculty of Mechanics and Mathematics, Moscow State University (MGU). Received the degrees of PhD in 1972 and doctor of science in 1987. Currently a professor and head of the Chair of Mathematical Physics of the Faculty of Computational Mathematics and Cybernetics, MGU. His main research interests lie in inverse and ill-posed problems in mathematical physics.     

Classifying the subjects of the Russian Federation on the basis of analysis of results of Gallup polling

The problem of processing of Gallup poll results by cluster analysis methods is considered. The aim of these polls, performed in different subjects of the Russian Federation, is to extract main characteristics of the regions. Demyanov Egor A. Born 1982. Graduated from the Moscow State University in 2004. Post-graduate student of the same university. Scientific interests: discrete mathematics and mathematical methods of pattern recognition. Author of two publications. Djukova Elena V. Born 1945. Graduated from the Moscow State University in 1967. Received candidate’s degree in Physics and Mathematics in 1979, Doctoral degree in Physics and Mathematics in 1997. Dorodnicyn Computing Center, Russian Academy of Sciences, leading researcher. Moscow State University, lecturer. Moscow Pedagogical University, lecturer. Scientific interests: discrete mathematics and mathematical methods of pattern recognition. Author of 76 papers. Peskov Nikolai V. Born 1978. Graduated from the Moscow State University in 2000. Received candidate’s degree in Physics and Mathematics in 2004. Dorodnicyn Computing Center, Russian Academy of Sciences, junior researcher. Scientific interests: discrete mathematics and mathematical methods of pattern recognition. Author of 17 papers. Inyakin Andrey S. Born 1978. Graduated from the Moscow State University in 2000. Received candidate’s degree in 2006. Dorodnicyn Computing Center, Russian Academy of Sciences, junior researcher. Scientific interests: discrete mathematics and mathematical methods of pattern recognition. Author of 16 papers.     

DCT-IV computation

A new fast algorithm for computing a type of discrete cosine transform applied to compute modified cosine transform is described. The number of arithmetic operations of the algorithm is estimated and interpreted. The computational scheme with substitution of variables is presented, and methods for optimizing the code for digital signal processors are proposed. Vasilii S. Shaptala. Born 1978. Graduated from St. Petersburg Bonch-Bruevich University for Telecommunications in 2000. Received his candidate’s degree in 2003. At present, he is a software engineer at ARC International R&D Center. Scientific interests: digital signal processing in telecommunication systems. Author of 15 publications. Mikhail V. Korman. Born 1974. Graduated from the Department of Mathematics and Mechanics of St. Petersburg State University in 1997. Attended his postgraduate courses at the same university in 1997–2000. At present, he is a director at ARC International R&D Center. Scientific interests: fast orthogonal transformations, information encoding, rate-distortion optimization (encoding error optimization), numerical methods. Author of 5 articles on methods of solving parabolic and hyperbolic equations numerically.     

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.     

Increasing the efficiency of combinatorial logical data analysis in recognition and classification problems

Problems of increasing the efficiency of combinatorial logical data analysis in recognition problems are examined. A technique for correct conversion of initial information for reduction of its dimensionality is proposed. Results of testing this technique for problems of real medical prognoses are given. Djukova Elena V. Born 1945. Graduated from Moscow State University in 1967. Candidate’s degree in Physics and Mathematics in 1979. Doctoral degree in Physics and Mathematics in 1997. Dorodnicyn Computing Center, Russian Academy of Sciences, leading researcher. Moscow State University, lecturer. Moscow Pedagogical University, lecturer. Scientific interests: discrete mathematics and mathematical method of pattern recognition. Author of 70 papers. Peskov Nikolai V. Born 1978. Graduated from Moscow State University in 2000. Candidate’s degree in 2004. Dorodnicyn Computing Center, Russian Academy of Sciences, junior researcher. Scientific interests: discrete mathematics and mathematical methods of pattern recognition. Author of ten papers. Inyakin Andrey S. Born 1978. Graduated from Moscow State University in 2000. Dorodnicyn Computing Center, Russian Academy of Sciences, junior researcher. Scientific interests: discrete mathematics and mathematical methods of pattern recognition. Author of ten papers. Sakharov Aleksei A. Born 1980. Graduated from Moscow State University in 2003. Moscow Pedagogical University, graduate student. Scientific interests: discrete mathematics and mathematical method of pattern recognition. Author of three papers.     

Effectiveness of consideration of deformations in problems of fingerprint identification

In the paper, we consider some refined methods for fingerprint recognition taking into account a distorting factor, namely, elastic deformations arising when a finger contacts with the scanner surface. We show that the consideration of elastic deformations significantly improves the quality of fingerprint recognition. Ushmaev Oleg Stanislavovich. Born 1981. Graduated from the Faculty of Mechanics and Mathematics of Lomonosov Moscow State University in 2002. Received candidate’s degree in 2004. Scientific interests: image processing, pattern recognition, biometrics. Author of 14 publications. Novikov Sergei Olegovich, Senior Researcher at the Institute of Information Problems RAS. Born in 1963. Graduated from the Moscow Institute of Physics and Technology in 1986. In 1990 finished the postgraduate study at the Institute of Information Problems, Russian Academy of Sciences. Candidate of Technical Sciences. Scientific interests: pattern recognition, image processing, mathematical modeling in biology. Author of two patents and more than 20 publications. Member of the International Scientific Societies SPI, IEEE Computer Society, IAPR.     

Computational complexity of the minimal committee problem and adjacent problems

The computational complexity of two important special cases of the minimal committee problem (MC), viz., the problem on the minimal committee of finite sets (MCFS) and the problem on the minimal committee of a system of linear algebraic inequalities (MCLE), is studied. Both problems are shown to be NP-hard. Separately, some adjacent problems of integer optimization are shown to be intractable. The efficient approximability threshold is estimated for the MCFS problem, the estimates being allied to the results known for the set cover problem. The intractable and polynomially solvable subclasses of the MCLE problem are given. The problem of the minimal affine separation committee (MASC) is considered in conclusion; the results obtained earlier for the MCLE problem are shown to be valid for this problem as well. Mikhail Yur’evich Khachai. Born 1970 in Krasnotur’insk, Sverdlovsk region. Graduated from the Faculty of Mathematics and Mechanics of Ural State University in Yekaterinburg in 1993 (Mathematics). Received his candidate’s degree (Mathematical Cybernetics) in 1996. Since 1994, he has been at the Institute of Mathematics and Mechanics of the Ural Division of the Russian Academy of Sciences. Since 1997, he has headed the Department of Pattern Recognition at the same institute. Scientific interests: theory and methods of pattern recognition learning, committee (perceptron) decision rules, and theory and methods of improper optimization problems. Author of more than 25 publications, including five in PRIA.     

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.     

Decision methods for some discrete extreme problems in recognition theory

By optimizing different models of recognition algorithms, a number of discrete extreme problems appear. The search for the maximum solvable subsystem of the system of linear inequalities is one of these tasks. The solution algorithm for this problem is described. This algorithm is effective for linear systems of small ranks. Also, an approximate method that is effective for systems of large dimensionality is proposed. The text was submitted by the author in English. Natalja N. Katerinochkina. Born 1945. Graduated from the Faculty of Mechanics and Mathematics, Moscow State University, in 1967. Received candidates degree in Physics and Mathematics in 1978. The senior scientific worker at the Dorodnicyn Computing Centre, Russian Academy of Science. Scientific interests: discrete mathematics, mathematical cybernetics, pattern recognition, discrete optimization. Author of 35 publications.     

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.     

Compensation for local defects in an image created using a triple-color photo technique

Problems connected with the creation of elements of technology for automated detection and the correction of image local defects obtained in the triple-color photo technique are considered. Automated procedures of detection and correction are developed. Procedures are implemented in software-tool and used in works on the reconstruction of S. M. Prokudin-Gorskii’s collection of photos taken in the early 20th century. Viktor Vasil’evich Minakhin. Born in 1948. Candidate of Sciences in physics and mathematics. Graduated from Faculty of Mechanics and Mathematics of Moscow State University in 1971 with a specialty in common control problems. Deputy Director at Restavrator-M Research and Restoration Center. Scientific interests include representations of noncommutatively algebraic structure, processing and analysis of images, image recognition, and architecture of databases. Author of 28 papers. Dmitrii Mikhailovich Murashov. Candidate of Sciences in engineering, associate professor. Born in 1958. Graduated from Moscow Aviation Institute in 1981 with a specialty in automatic control systems. He works at Dorodnitsyn Computing Center of the Russian Academy of Sciences, Moscow. Scientific interests include automatic control, processing and analysis of the images, and image recognition. Author of 50 papers. Yurii Pavlovich Davidov. Born in 1964. Graduated from Moscow Aviation Institute in 1987 with a specialty in radio engineering. 1989–1999 worked for the Scientific Council on the Complex Problem of Cybernetics at the Russian Academy of Sciences. Since 1996, he has worked at Restavrator-M Ltd. Scientific interests include the development of Image databases; development of software for 3D reconstruction and processing data of geodesic measurements; and software for color registration, color correction, and the removal of image defects. Dmitrii Abramovich Dimentman. Born in 1962. Graduated from Moscow State Historical-Archive Institute in 1990 with a specialty in historical archiving. Since 1979, he has worked at the State Historical Museum, Moscow, currently as the curator of author negatives in the arts department and leading researcher. Scientific interests include photo history and the study of photo document collections. Author of 20 papers.     

Probability-theoretical and possibility-theoretical algorithms for reducing multivariate data: A comparative analysis

A comparative analysis of probability-theoretical and possibility-theoretical methods for reducing multivariate data is carried out. Konstantin Sergeevich Sobolev. Born 1976. Graduated from the Moscow State University in 2000. Author of two papers. Ol’ga Vladimirovna Mondrus. Born 1981. Graduated from the Moscow State University in 2005. Author of two papers. Yurii P. Pyt’ev. Graduated from the Faculty of Physics, Moscow State University. Professor, Head of the Department of Computer Methods in Physics, Faculty of Physics, Moscow State University. Scientific Interests: mathematical methods of data analysis and interpretation, mathematical modeling of measuring-computing systems of superhigh resolution, and fuzzy and uncertain fuzzy mathematics. Author of more than 300 publications on mathematics, mathematical physics, and information science, including several monographs.     

Identification of inorganic salts and determination of their concentrations in aqueous solutions based on the valence Raman band of water using artificial neural networks

The characteristic features of the valence Raman band of water in the solutions of electrolytes are revealed. These features allow the noncontact recognition of the type of salt and the determination of its concentration in aqueous solutions using artificial neural networks. Viktor V. Fadeev. Born 1935. Graduated from the Physics Faculty of Moscow State University in 1959. Received candidate’s degree in 1967 and doctoral degree in 1983. Professor of the Physics Faculty, Moscow State University. Scientific interests: optics, laser physics, spectroscopy, and inverse problems. Author of more than 300 papers and a discovery diploma. Laureate of the USSR State Prize (1983). Tat’yana A. Dolenko. Born 1961. Graduated from the Physics Faculty of Moscow State University in 1983. Received candidate’s degree in 1987. Senior Researcher of the Physics Faculty, Moscow State University. Scientific interests: laser spectroscopy, Raman spectroscopy of aqueous media, inverse problems, and artificial neural networks. Author of 57 papers and an invention certificate. Laureate of the Lenin Komsomol Prize (1985). Sergei A. Burikov. Born 1978. Graduated from the Physics Faculty of Moscow State University in 2002. Junior Researcher of the Physics Faculty, Moscow State University. Scientific interests: optics, Raman spectroscopy of aqueous media, inverse problems, and artificial neural networks. Author of 14 papers. Aleksandr V. Sugonyaev. Born 1982. Graduated from the Physics Faculty of Moscow State University in 2005. Scientific interests: Raman spectroscopy of aqueous media, inverse problems, and artificial neural networks. Author of 5 papers.     

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

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

Algorithm of adaptive morphological filtering of images

A general approach to the problem of analysis of images which are piecewise-constant with respect to some feature is described. Algorithms for solving this problem are presented. The algorithm proposed is illustrated by the following examples: the problem of noise suppression on images with piecewise-polynomial brightness; the problem of localization of an unknown object in an image with a given background image, which may be obtained under different lighting conditions; and the problem of random field segmentation. The results obtained by these algorithms on real images are not worse than those obtained by existing algorithms. Igor I. Falomkin. Born 1979. Graduated from the Faculty of Physics, Moscow State University in 2001. Scientific interests: image analysis and recognition, analysis and interpretation of experimental data. Yurii P. Pyt’ev. Graduated from the Faculty of Physics, Moscow State University. Professor, Head of the Department of Computer Methods in Physics, Faculty of Physics, Moscow State University. Scientific interests: mathematical methods of data analysis and interpretation, mathematical modeling of measuring-computing systems of superhigh resolution, and fuzzy and uncertain fuzzy mathematics. Author of more than 300 publications on mathematics, mathematical physics, and information science, including several monographs.