Using complex and hypercomplex systems in image and signal processing

New approaches to processing of dense and point images are presented. They are based on the theory of hypercomplex numbers and make use of simplified but reasonably adequate image models that incur no significant loss of information. The advantage of these approaches consists in increased efficiency of decisions made by machine vision systems and in considerable reduction of time needed to arrive at these decisions. The basics of the theory of complex-valued (contour) and quaternion-valued signals are considered. We show how this theory is related to the theory of real-valued signals and identify the problems where hypercomplex signals have advantages over real-valued ones. Yakov A. Furman. Born 1939. Graduated from the Taganrog Radioengineering Institute in 1961. Received doctoral degree (Dr. Sci. (Eng.)) in 1989. Professor, Head of the Chair of Radioengineering Systems, Maryi State Technical University. Scientific interests: digital processing and synthesis of signals and images, pattern recognition. Author of more than 66 papers and two monographs. Corresponding member of the Russian Engineering Academy, member of the Editorial Board of Vestnik Verkhne-Volzhskogo otdeleniya Akademii tekhnologicheskikh nauk RF. In 2002 awarded the order of Druzhba Narodov and, in 1995, a medal of the order Za zaslugi pered Otechestvom II stepeni. Aleksandr V. Krevetskii. Born 1966. Graduated from Maryi State Technical University in 1990. Received candidates degree (Cand. Sci. (Eng.)) in 1995. Docent, Head of the Chair of Informatics, Maryi State Technical University. Scientific interests: digital processing and synthesis of signals, image analysis, pattern recognition. Author of more than 25 papers and two monographs.     

Search algorithm and the distortion analysis of fine details of real images

This work describes a search algorithm and a method of the distortions analysis of fine details of real images based on objective criteria. The article is published in the original. Sergei V. Sai. Born 1960. Graduated from Tomsk Institute of Automated Control Systems and Radio Electronics (TIACSRE) in 1983 (Radio Electronic Devices). Received candidateís degree in 1990 and doctoral degree in 2003. Head of Computer Engineering Chair at Khabarovsk State Technical University (KhSTU). Scientific interests: digital image analysis and processing. Author of 56 scientific publications, including 2 monographs. Member of Editorial Board of the journal “Telekommunikatsii.” Nikolay Yu. Sorokin. Born in 1977. Khabarovsk State University of Technology, 1999. University of Saarland, M.Sc., 2002. University of Saarland, Dr.-Ing., 2003. At present time he is an associate professor at Computer Technique chair at Pacific National University. His scientific interests include embedded systems, FPGA, image processing. N.Yu. Sorokin is an author of more than 30 scientific publications including one book.     

Cluster analysis of results of ultrasonic testing

The methods of cluster and correlation analysis are employed to solve various problems related to the processing of results obtained using the computerized ultrasonic testing of welded joints. In particular, the principal component analysis, K-means algorithm, and support vector machine are considered. A detailed analysis of the methods and the main results are presented. Aleksandr O. Skomorokhov. Born 1951. Graduated from the Faculty of Radio Physics, Nizhni Novgorod State University in 1973. Received candidate’s degree in 1984. Associate Professor of the Obninsk State Technical University of Atomic Energy. Scientific interests: development and application of modern methods for data analysis, technical diagnostics, and matrix programming languages. Author of 30 papers. Member of SIGAPL, SIGKDD, ACM, BCS, and the Russian Association of Artificial Intelligence. Pavel A. Belousov. Born 1979. Graduated from the Obninsk Institute of Atomic Power Engineering in 2002. PhD student of the Obninsk State Technical University of Atomic Energy. Author of three papers. Winner of the Obninsk Stipend for Students, PhD Students, and Young Lecturers. Aleksandr V. Nakhabov. Born 1979. Graduated from the Obninsk Institute of Atomic Power Engineering in 2002. PhD student of the Obninsk State Technical University of Atomic Energy. Author of three papers. Winner of the Federal Stipend of the Potanin Foundation.     

Autocorrelated images and search for distance between them in speech command recognition

The paper considers the application of autocorrelated images for the recognition of speech commands; it also considers the dependence of the quality of speech recognition on metrics used to estimate the distance between the lines of autocorrelated images by a method based on dynamic programming. Viktor Rostislavovich Krasheninnikov. Born 1945, Dr. of Techn. Sci. (1996), Professor (1997), Head of the Chair of the Systems of Automated Designing (SAPR), Ulyanovsk State Technical University, scientific interests include: statistical analysis of multidimensional images and fields. At present has 160 publications. Andrei Igorevich Armer. Born 1982, Cand. of Techn. (2006), Docent of the Chair of SAPR of the Ulyanovsk State Technical University (2007), scientific interests include: processing and analysis of speech signals, pattern recognition. At present has 21 publication. Vyacheslav Vladimirovich Kuznetsov. Born 1983, 2006 degree from the Ulyanovsk State Technical University. At present a post-graduate student of the Chair of Systems of Automatic Designing, Ulyanovsk State Technical University. The area of scientific interests includes: speech recognition, autocorrelated images, neutron networks. Has 7 publications.     

Stereophotogrammetric 3D real-time machine vision

Signal processing algorithms often have to be modified significantly for implementation in hardware. Continuous real-time image processing at high speed is a particularly challenging task. In this paper a hardware-software codesign is applied to a stereophotogrammetric system. To calculate the depth map, an optimized algorithm is implemented as a hierarchical-parallel hardware solution. By subdividing distances to objects and selecting them sequentially, we can apply 3D scanning and ranging over large distances. We designed processor-based object clustering and tracking functions. We can detect objects utilizing density distributions of disparities in the depth map (disparity histogram). Motion parameters of detected objects are stabilized by Kalman filters. The text was submitted by the authors in English. Michael Tornow was born in Magdeburg, Germany, in 1977. He received his diploma engineer degree (Dipl.-Ing.) in electrical engineering at the University of Magdeburg, Germany, in 2002. He is currently working on a PhD thesis focusing on hardware adapted image processing and vision based driver assistance. Robert W. Kuhn received his diploma engineer degree (Dipl.-Ing.) in geodesy at the Technical University of Berlin, Germany, in 2000. His current work on a PhD thesis focuses on calibration and image processing. Jens Kaszubiak was born in Blankenburg, Germany, in 1977. He received his diploma engineer degree (Dipl.-Ing.) in electrical engineering at the University of Magdeburg, Germany, in 2002. His current research work focuses on vision-based driver assistance and hardware-software codesign. Bernd Michaelis was born in Magdeburg, Germany, in 1947. He received a Masters Degree in Electronic Engineering from the Technische Hochschule, Magdeburg, in 1971 and his first PhD in 1974. Between 1974 and 1980 he worked at the Technische Hochschule, Magdeburg, and was granted a second doctoral degree in 1980. In 1993 he became Professor of Technical Computer Science at the Otto-von-Guericke University, Magdeburg. His research work concentrates on the field of image processing, artificial neural networks, pattern recognition, processor architectures, and microcomputers. Professor Michaelis is the author of more than 150 papers. Gerald Krell was born in Magdeburg, Germany, in 1964. He earned his diploma in electrical engineering in 1990 and his doctorate in 1995 at Otto-von-Guericke University of Magdeburg. Since then he has been a research assistant. His primary research interest is focused on digital image processing and compression, electronic hardware development, and artificial neural networks.     

Some modifications of the algorithm for construction of classification trees

Some modifications of the algorithm for constructing classification trees that are helpful in the processing of noise spectra in the technical diagnostics of the nuclear power plant are presented. Aleksandr O. Skomorokhov. Born 1951. Graduated from the Faculty of Radio Physics, Nizhni Novgorod State University in 1973. Received candidate’s degree in 1984. Associate Professor of the Obninsk State Technical University of Atomic Energy. Scientific interests: development and application of modern methods for data analysis, technical diagnostics, and matrix programming languages. Author of 30 papers. Member of SIGAPL and SIGKDD of ACM, BCS, and the Russian Association of Artificial Intelligence. Vladimir N. Kutinsky. Born 1975. Graduated from the Obninsk Institute of Atomic Power Engineering in 1998. Senior Lecturer of the Obninsk State Technical University of Atomic Energy. Author of three papers. Member of the Russian Association of Artificial Intelligence. Winner of the Obninsk Stipend for Students, PhD Students, and Young Lecturers. Mikhail T. Slepov. Born 1966. Graduated from the Obninsk Institute of Atomic Power Engineering in 1992. Received candidate’s degree in 1999. Head of the Laboratory of Technical Diagnostics at the Novovoronezhskaya Nuclear Power Plant. Scientific interests: vibration analysis, signal processing, spectra. Author of seven papers. Member of Advisory Committee of the Rosenergoatom Concern.     

Pseudogradient optimization in the estimation of geometric interframe image deformations

In the pseudogradient estimation of image parameters, the convergence of the estimates and the computational costs depend on the size of a local sample of image counts used to determine the pseudogradient of the objective function. An approach to pseudogradient optimization via choosing a plan of counts in the local sample is proposed. Aleksandr Grigor’evich Tashlinskii. Born 1954. Graduated from Ul’yanovsk State Technical University in 1977. Received doctoral degree in 2000. Professor of the Department of CAD Systems at Ulyanovsk State Technical University. Research interests: statistical image processing, in particular, the estimation of spatiotemporal deformations in dynamic image sequences. Author of about 250 publications, including 80 papers and 2 monographs covering the parameter estimation of spatial deformations in image sequences. Full member of the International Academy of Authors of Scientific Discoveries and Inventions and the Russian Academy of Natural Sciences. Awarded medals from these academies. Galina Leonidovna Minkina. Born 1983. Graduated from Ul’yanovsk State Technical University in 2005. Graduate student of this university. Research interests: optimization of parameters of algorithms for estimating geometrical interframe image deformations. Author of 25 publications. Galina Vladimirovna Dikarina. Born 1983. Graduated from Ul’yanovsk State Technical University in 2005. Graduate student of this university. Research interests: adaptive estimation of quantile random fields. Author of eight publications. Aleksandr Nikolaevich Repin. Born 1985. Graduated from Ul’yanovsk State Technical University in 2007. Graduate student of this university. Research interests: minimization of computational costs in the estimation of geometrical interframe image deformations and the prediction of cellular coverage. Author of four publications.     

Preparation of templates in speech command recognition by single- and double-channel scheme in background noise

One of the methods for speech command (SC) recognition against a very noisy background is to compare SCs to their templates stored in a database. There is no noise in the templates, so their pauses can be determined precisely. The recognized SCs are noisy, and their pauses are determined with errors. In recognition, the SC pauses should match the template pauses. To achieve this, it is suggested that noise be added to templates and template pauses be redetermined by the same method. This noise is taken from the second microphone located at a distance from the basic one and receiving noise clean of speech signal. Our studies have shown the proposed procedures to improve the quality of SC recognition. Viktor Rostislavovich Krasheninnikov. Born 1945, Dr. of Techn. Sc. (1996), Professor (1997), Head of the Chair of the Systems of Automated Designing (SAPR), Ulyanovsk State Technical University, scientific interests include: statistical analysis of multidimensional images and fields. At present has 160 publications. Andrey Igorevich Armer. Born 1982, Cand. of Techn. (2006), Docent of the Chair of SAPR of the Ulyanovsk State Technical University (2007), scientific interests include: processing and analysis of speech signals, pattern recognition. At present has 21 publication. Aleksey Vasil’evich Khvostov. Post-graduate student of the Chair of SAPR, Ulyanovsk State Technical University, scientific interests include: detection of signals, processing and analysis of speech signals. At present has 10 publication.     

Evaluation of local dependencies of images wavelet decomposition

An approach to identifying local area structure that is used in the spatial interaction models adapted to the image characteristic properties using mutual information criterion is reviewed in this article. Experimental results that demonstrate the value of using the represented method are shown. The text was submitted by authors in English. Arcady Lvovich Zhiznyakov. Candidate of engineering science. Docent of the Department of Information Systems at the Murom Institute of Vladimir State University. The field of science interests is digital image processing and analysis. He is the author of more than 150 science publications. Vasilii Evgenevich Gai. A postgraduate student of the Department of Information Systems at the Murom Institute of Vladimir State University. The field of science interests is digital image processing and analysis. He is the author of about 40 science publications. Sultan Sadykovich Sadykov. Doctor of engineering science, professor. Professor of the Department of Information Systems at the Murom Institute of Vladimir State University. The field of science interests is digital image processing and analysis. He is the author of more than 200 science publications.     

The specifics of pseudogradient estimation of geometric deformations in image sequences

The parameter estimation of geometric deformations of image sequences is of interest in itself and is part of the solution to many other problems in image processing and analysis. In this paper, the opportunities and specifics of pseudogradient computation are analyzed, and a comparative analysis of different computational methods is presented. Aleksandr Grigor’evich Tashlinskii. Born 1954. Graduated from the Ulyanovsk State Technical University in 1977. Received doctoral degree in 2000. Professor of the Department of CAD Systems at the Ulyanovsk State Technical University. Research interests: statistical image processing, in particular, the estimation of spatiotemporal deformations in dynamic image sequences. Author of about 250 publications, including 80 papers and 2 monographs covering the parameter estimation of spatial deformations in image sequences. Full member of the International Academy of Authors of Scientific Discoveries and Inventions and the Russian Academy of Natural Sciences. Awarded medals from both academies.     

Automatic Image-Based Pencil Sketch Rendering

This paper presents an automatic image-based approach for converting greyscale images to pencil sketches,in which strokes follow the image features.The algorithm first extracts a dense direction field automatically using Logical/Linear operators which embody the drawing mechanism.Next,a reconstruction approach based on a sampling-and-interpolation scheme is introduced to generate stroke paths from the direction field.Finally,pencil strokes are rendered along the specified paths with consideration of image tone and artificial illumingation.As an important application,the technique is applied to render portraits from images with little user interaction.The experimental results demonstrate that the approach can automatically achieve copmelling pencil sketches from reference images.     

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.     

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.     

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.     

Analyzing rendition quality of fine details of MPEG-4 image

A solution to the problem of analyzing the rendition quality of fine details of color images on the basis of objective criteria is proposed. The results of experimental estimation of MPEG-4 image quality obtained by software analyzer are given. Sergei V. Sai. Born 1960. Graduated from Tomsk Institute of Automated Control Systems and Radio Electronics (TIACSRE) in 1983 (Radio Electronic Devices). Received candidateís degree in 1990 and doctoral degree in 2003. Head of Computer Engineering Chair at Khabarovsk State Technical University (KhSTU). Scientific interests: digital image analysis and processing. Author of 56 scientific publications, including 2 monographs. Member of Editorial Board of the journal “Telekommunikatsii.”     

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.     

Handwritten signature verification based on code representation

A method to obtain a code representation of handwritten signatures is described and an algorithm for signature verification based on such representations is proposed. Results of tests to determine efficient methods of image compression for the purpose of signature verification are presented. Konstantin Alekseev. Born 1979. Received Master’s degree in engineering and technology (Radioengineering) in 2002. Currently post-graduate student at St. Petersburg State Electrotechnical University “LETI”, chair of television and video. Scientific interests: digital image processing and pattern recognition. Author of three papers. Svetlana Egorova. Born 1931. Graduated from St. Petersburg State Electrotechnical University “LETI” in 1955, received Candidates degree (Eng.) in 1965; since 1968 a senior lecturer at the chair of television and video, St. Petersburg State Electrotechnical University “LETI”. Scientific interests: optical and digital image processing and compression methods in signal processing. Author of 141 papers.     

Wavelet filtering of the structure signs of an image

In this article, an approach to filtering the edges of a halftone image is presented. The proposed approach is based on using a packet wavelet transformation of one-dimensional signals with any scale factor. The text was submitted by the authors in English. Arcady Lvovich Zhiznyakov. Candidate of engineering science. Docent of the Department of Information Systems at the Murom Institute of Vladimir State University. The field of science interests is digital image processing and analysis. He is the author of more than 150 science publications. Andrei Alexandrovich Fomin. A post-graduate student of the Department of Information Systems at the Murom Institute of Vladimir State University. The field of science interests is digital image processing and analysis. He is the author of more than 40 science publications.     

Estimating directions of optic disk blood vessels in retinal images

The problem of determining directions of blood vessels in the optic disk is considered. The proposed method for estimating the vessel directions is based on analyzing local minima of gray-scale profile of the eye-ground image. Results of tests on real images are presented. Mikhail Anan’in. Born 1984. Graduated from the Samara State Aerospace University in 2007 and is currently a post-graduate student at the same university. From 2006 to present is a junior researcher at the Image Processing Systems Institute, Russian Academy of Sciences. Scientific interests: image processing, image reconstruction, pattern recognition, wavelet analysis, and differential geometry. Authored more than ten papers. Nataliya Il’yasova. Born 1966. Graduated from the Samara State Aerospace University in 1991, where in 1997 she received candidate’s degree (Eng.). Currently a senior s researcher at the Image Processing Systems Institute, Russian Academy of Sciences and a senior lecturer at Samara State Aerospace University. Scientific interests: digital image processing and recognition, pattern recognition, information systems in biomedical applications, computer-aided systems for monitoring eye fundus microvascular morphology, and analysis of cardiac coronary vessels. Author of more than 60 papers in the field of image processing and pattern recognition. Aleksandr Kupriyanov. Born 1978. Graduated from the Samara State Aerospace University in 1991 and in 1997 received candidate’s degree (Eng.) from the same university. Currently has a position of researcher at the Image Processing Systems Institute, Russian Academy of Sciences. Scientific interests: digital image processing and recognition, pattern recognition, information systems in biomedical applications, computer-aided systems for monitoring eye fundus microvascular morphology, analysis of cardiac coronary vessels, evaluation of diagnostic features, and retinal image analysis. Author of more than 30 papers in the field of image processing and pattern recognition.