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.     

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.     

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.     

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.     

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.     

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.     

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.     

An algorithm for median filtering on the basis of merging of ordered columns

This paper presents algorithms for optimization of the median filtering of images. A median filtering algorithm on the basis of merging ordered columns of an image in the 3 × 3 window of a filter is developed, which allows us to perform the filtering on a personal computer in real time without use of additional hardware. This algorithm outperforms other median filtering algorithms in execution speed on a personal computer. Zalesky Boris Andreevich. Born 1953. Graduated from the Lomonosov Moscow University in 1979. Received the candidate’s degree in 1982 and doctoral degree in Physics and Mathematics in 1990. Leading researcher at the United Institute of Informatics Problems of the National Academy of Sciences of Belarus. Scientific interests: image processing, pattern recognition. Author of 81 papers. In 1987 awarded Leninskii Komsomol prize in the area of mathematics. Kravchonok Aleksandr Ivanovich. Born 1982. Graduated from the Belarussian State University in 2004. Junior researcher at the United Institute of Informatics Problems of the National Academy of Sciences of Belarus. Scientific interests: image processing, pattern recognition. Author of two papers. Lukashevich Pavel Vladimirovich. Born 1982. Graduated from the Moscow Institute of Physics and Technology in 2005. Junior researcher at the United Institute of Informatics Problems of the National Academy of Sciences of Belarus. Scientific interests: image processing, pattern recognition. Author of one paper.     

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.     

Prediction of strong earthquakes with the use of the scalar product of matrices with a sliding window

The paper is devoted to the important problem of predicting strong earthquakes in space and time. The solution is based on the hypothesis that the prehistory of strong earthquakes in some region implicates a complex sequence of previous moderate-power earthquakes that is certain to considerable extent and common for various strong earthquakes in this region. The algorithm for finding this commonality is implemented by means of procedures on Boolean matrices with a sliding window and has been approved for the earthquakes in Kamchatka and the Kuril Islands. Sliding examination neatly reveals almost all strong earthquakes that have a long enough prehistory (12 years). It is interesting that such earthquakes are predicted several years prior to the catastrophe with an accuracy of 1 or 2 days in time and 100 km in space. There are no false maxima. “There is a striking possibility of mathematically treating an object without understanding its essence.” A. Einstein Aleksandr Mikhailovich Shurygin. Born 1931. Graduated from Moscow State University, Faculty of Geology (1949–1954) and Faculty of Mechanics and Mathematics (1960–1965). Received candidate’s degree in Geology and Mineralogy (Tectonics) in 1959 and doctoral degree (Information Theory) in 2002. Since 1970, he has had the title of Senior Researcher. He works as a leading researcher at the Faculty of Computational Mathematics and Cybernetics of MSU and as a senior researcher at the Scientific Council of Cybernetics of the RAS. Author of more than 130 scientific publications, including five monographs. Strigunova Mariya S. Born 1976. Graduated from Moscow State University in 1998. Moscow State Academy of Publishing, the Department of Higher Mathematics, assistant. Scientific Council on Cybernetics, Russian Academy of Sciences, applicant for dissertation. Author of nine publications.     

A Cramer-Rao bound for the measurement accuracy of motion parameters and the accuracy of reconstruction of a surface profile observed by a binocular vision system

A lower bound for the measurement errors motion parameters and of the observed surface profile is constructed as a function of the parameters of a binocular computer vision system (CVS) and observation conditions. This bound justifies the specification of the CVS parameters and allows one to formulate constraints on the trajectory of an object based on the required accuracy characteristics of the CVS. Vladimir Aleksandrovich Grishin. Born 1960. Graduated from the Moscow Institute of Radioengineering, Electronics, and Automation (Technical University) in 1983 and the Faculty of Mechanics and Mathematics, Lomonosov Moscow State University, in 1988. Received candidate’s degree in 1995. Currently is with the Space Research Institute (IKI), Russian Academy of Sciences, as a senior scientist. Partly employed at the Bauman Moscow State Technical University as a lecturer. Scientific interests: application of the methods of artificial intelligence to high-precision navigation and control of unmanned aerial vehicles and robots; profile-metric navigation systems; application of machine vision and image recognition methods to motion control problems. Author of more than 40 publications, including 5 inventions. Has been engaged as a referee in the organizing committees of the of the following conferences: World Multi-Conference on Systemics, Cybernetics and Informatics, International Conference on Computing, Communication and Control Technologies, and in the editorial board of the Journal of Systemics, Cybernetics, and Informatics published by the International Institute of Informatics and Systemics.     

Stochastic filtering of approximate symmetries in dense packings of clusters

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

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.     

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.     

A generalization of segmentation methods of quantiles and modes to the case of several images

The problem of segmentation by several images is considered for fragments of a scene containing a given object and its neighborhood. To solve this problem, generalizations of the well-known methods of quantiles and modes are proposed that are constructed on the concept of random distance. The results of computer experiments on the segmentation of model and quasireal scenes by the methods proposed are compared. Vyatcheslav Borisovich Fofanov. Born 1948. Graduated from the Kazan State University in 1971. Received candidate’s degree in engineering in 1977. Currently is an assistant professor at Kazan State University. Scientific interests: pattern recognition and image deciphering. Author of more than 40 publications. Ramil’ Fuatovich Kuleev. Born 1985. Graduated from the Kazan State University in 2007. Currently is a postgraduate student at the Chair of Economical Cybernetics, Kazan State University. Scientific interests: pattern recognition and image deciphering. Author of eight publications.     

Optimal signal interpolation using the values of signal and its derivative

The effect of the bias in a sequence of signal samples and sequence of signal derivative samples on the signal reconstruction accuracy is considered for a bandwidth-limited signal. Vitalii M. Efimov. Born 1933. Graduated from the Moscow Institute of Aviation. Received candidate’s degree in 1964. Leading researcher at the Institute of Automatics and Electrometry, Siberian Division, Russian Academy of Sciences. Scientific interests: signal sampling and quantization and processing and squeezing of digital data. Author of 85 papers. Aleksandr L. Reznik. Born 1948. Graduated from Novosibirsk State University in 1969. Received candidate’s degree in 1981. Head of the laboratory of the Institute of Automatics and Electrometry, Siberian Division, Russian Academy of Sciences. Scientific interests: analytical and numerical methods for solving complex probability problems with computer calculations. Author of 64 papers. Andrei V. Torgov. Born 1959. Graduated from Novosibirsk State University in 1983. Leading software engineer at the Institute of Automatics and Electrometry, Siberian Division, Russian Academy of Sciences. Scientific interests: image processing and digital filtering. Author of 17 papers.     

Unsupervised classification of image texture

An automatic histogram-based algorithm for clustering statistical textural features of image incorporating estimation of the quality of the obtained distribution of feature vectors over clusters is presented. The algorithms is applied to classification of forest aerial imagery. Valeriya S. Sidorova. Born 1947. Graduated Novosibirsk State University in 1972. Researcher at Institute of Computational Mathematics and Mathematical Geophysics. Scientific interests: classification of remote sensing data, texture analysis, and 3D visualization. Author of 40 papers.     

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

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

Choice of the objective function for pseudogradient measurement of image parameters

Approaches to the choice of objective functions and the form of the pseudogradient are considered for pseudogradient evaluation of interframe geometrical image deformations. The possibilities of reducing the computational cost of calculation of the pseudogradient are analyzed. Minkina Galina Leonidovna. Born in 1983. Fifth-year student at Ulyanovsk State Technical University, specialty applied mathematics. Scientific interests: optimization of parameters of algorithms for estimating interframe geometrical image deformations. Samoilov Mikhail Yurievich. Born in 1981. Graduated from Moscow State University in 2003. PhD student at Ulyanovsk State Technical University. Scientific interests: minimization of the computational cost in estimation of interframe geometrical image deformations. Tashlinskii Alexander Grigorievich. Born in 1954. Graduated from the Ulyanovsk Polytechnical Institute in 1977. Received doctoral degree in 2000. Professor in the Department of Systems of Computer Aided Design. Scientific interests: statistical image processing, in particular, estimation of spatiotemporal deformations of sequences of dynamical images. Author of 200 publications, including more than 60 papers and a monograph on estimation of parameters of spatial deformations of sequences of images. Full member of the International Academy of Authors of Scientific Discoveries and Investigations and of the Russian Academy of Natural Sciences. Awarded medals from these academies.