A comparison between the first absolute central moment and the gradient of Gaussian when detecting edges in presence of Gaussian noise

The gray-level absolute central moment of the first order provides ridges at gray-level discontinuities as well as a conventional gradient of Gaussian (GoG). A mass center b of the gray-level variability can also be associated to the first absolute central moment. When given a starting point p, vector b indicates the path which joins p to the nearest gray-level discontinuity as well as the gradient of the GoG magnitude. However, when the right configuration of the operator is chosen, vector b indicates a point which is closer to the discontinuity than p, regardless of the distance between p and the discontinuity. Therefore, when using vector b, gray-level discontinuities can be located with an iterative approach. In this paper, the edge detection properties of the first absolute central moment are compared with those of the GoG. The text was submitted by the authors in English. Marcello Demi was born in Cecina, Italy, in 1956. He graduated in electronic engineering from the University of Florence, Italy, in 1985. He is currently head of the Computer Vision Group at the CNR Institute of Clinical Physiology in Pisa, senior scientist for ESAOTE Spa, and he teaches a course on medical image processing at the Faculty of Applied Physics, University of Pisa. His research interests are cardiovascular image processing systems, contour tracking of moving deformable objects, and filtering schemes inspired by the early stages of biological vision systems. He has 80 scientific publications and his objective is the development of common projects with people who work in the area of biological vision for the purpose of both understanding biological vision and developing image processing systems. Francesco Faita was born on June 28, 1973, in La Spezia (Italy). In 2001, he graduated from Universitá degli Studi di Pisa obtaining the degree of electronic engineer. Since 2001, he has been working as a research fellow at the Institute of Clinical Physiology of the Italian National Research Council. His main research interests lie in computer vision, in particular, in the field of ultrasound imaging. Elisabetta Bianchini was born in Lucca, Italy, in 1975. She received her degree in electronic engineering from the University of Pisa, Italy, in 2004. Since 2004, she has been a junior researcher at CNR, the Italian National Research Council, at the DSP lab in IFC (Institute of Clinical Physiology). Vincenzo Gemignani was born on October 10, 1969, in Viareggio (Italy). In 1995, he graduated from Universitá degli Studi di Pisa obtaining the degree of electronic engineer. Since 1996, he has been working as a research fellow at the Institute of Clinical Physiology of the Italian National Research Council. His main research interests lie in digital signal processing, in particular, in field real-time image analysis.     

Fast correction of bleed-through distortion in grayscale documents by a blind source separation technique

Ancient documents are usually degraded by the presence of strong background artifacts. These are often caused by the so-called bleed-through effect, a pattern that interferes with the main text due to seeping of ink from the reverse side. A similar effect, called show-through and due to the nonperfect opacity of the paper, may appear in scans of even modern, well-preserved documents. These degradations must be removed to improve human or automatic readability. For this purpose, when a color scan of the document is available, we have shown that a simplified linear pattern overlapping model allows us to use very fast blind source separation techniques. This approach, however, cannot be applied to grayscale scans. This is a serious limitation, since many collections in our libraries and archives are now only available as grayscale scans or microfilms. We propose here a new model for bleed-through in grayscale document images, based on the availability of the recto and verso pages, and show that blind source separation can be successfully applied in this case too. Some experiments with real-ancient documents arepresented and described. Anna Tonazzini graduated cum laude in Mathematics from the University of Pisa, Italy, in 1981. In 1984 she joined the Istituto di Scienza e Tecnologie dell'Informazione of the Italian National Research Council (CNR) in Pisa, where she is currently a researcher at the Signals and Images Laboratory. She cooperated in special programs for basic and applied research on image processing and computer vision, and is co-author of over 60 scientific papers. Her present interest is on inverse problems theory, image restoration and reconstruction, document analysis and recognition, independent component analysis, neural networks and learning. Emanuele Salerno graduated in Electronic Engineering from the University of Pisa, Italy, in 1985. In September 1987 he joined the Italian National Research Council (CNR) at the Department of Signal and Image Processing, Information Processing Institute (now Institute of Information Science and Technologies, ISTI, Signals and Images Laboratory), Pisa, Italy, where he has been working in applied inverse problems, image reconstruction and restoration, microwave nondestructive evaluation, and blind signal separation. He has been assuming different responsibilities in research programs in nondesctructive testing, robotics, numerical models for image reconstruction and computer vision, neural networks techniques in astrophysical imagery. At present, he is local scientific responsible in the framework of the European Space Agency's “Planck Surveyor Satellite” mission, and takes part in the European CRAFT project “ISyReADeT”, for document image restoration. Luigi Bedini graduated cum laude in Electronic Engineering from the University of Pisa, Italy, in 1968. Since 1970 he has been a Researcher of the Italian National Research Council, Istituto di Scienza e Tecnologie dell'Informazione, Pisa, Italy. His interests have been in modelling, identification, and parameter estimation of biological systems applied to non-invasive diagnostic techniques. At present, his research interest is in the field of digital signal processing, image reconstruction and neural networks applied to image processing. He is co-author of more than 80 scientific papers. From 1971 to 1989, he was Associate Professor of System Theory at the Computer Science Department, University of Pisa, Italy.     

Synthesising surface matching algorithms using the correspondence framework

Computer vision tasks such as registration, modeling and object recognition, are becoming increasingly useful in industry. Each of these applications employs correspondence algorithms to compute accurate mappings between partially overlapping surfaces. In industry, it is essential to select an appropriate correspondence algorithm for a given surface matching task. A correspondence framework has recently been proposed to assist in the selection and creation of correspondence algorithms for these tasks. This paper demonstrates how to use the correspondence framework to create a new surface matching algorithm, which uses stages of an existing model matching algorithm. The efficiency with which the new algorithm is created using the correspondence frame work is emphasized. In addition, results show that the new algorithm is both robust and efficient. The text was submitted by the authors in English. Birgit Maria Planitz, born in 1978, received B. Engineering (Hons) degree at the Queensland University of Technology (QUT) in Brisbane, Australia (2001). Dr. Planitz then continued her studies at QUT, enrolling in a PhD. The PhD was in the field of computer vision, specializing in three-dimensional surface matching. Dr. Planitz graduated from her postraduate degree in 2005, with two major journal publications, six conference papers and a technical report. She is currently working for the e-Health Research Centre/CSIRO ICT Centre. Dr. Planitz is a member of the Australia Pattern Recognition Society. Anthony John Maeder, born 1958, graduated with B. Science (Hons) from University of Witwatersrand in 1980 and M. Science from the University of Natal in 1982. He was awarded his PhD in 1992 by Monash University. Dr. Maeder is currently the Research Director, E-Health Research Centre/CSIRO ICT Centre and Adjunct Professor, Faculty of Health Sciences, University of Queensland. His research areas include digital image processing, image and video compression, medical imaging, computer graphics and visualization. Dr. Maeder has 200 publications consisting of 10 monographs and proceedings, 20 journal papers and 180 conference papers. He is a fellow of the Institution of Engineers Australia; a member of IEEE, ACM, ACS, HISA; a member of SPIE International Technical Committee for Medical Imaging; and a member of national executive committee of the Australian Pattern Recognition Society. John Alan Williams, born in 1973, was awarded his PhD from the Queensland University of Technology (QUT), Australia, in 2001. He was previously awarded undergraduate degrees in Electronic Engineering and Information Technology (Hons), also from QUT, in 1995. He is currently employed at the School of ITEE at The University of Queensland, Brisbane, Australia, where he holds the position of Research Fellow. Dr. William’s research interests include reconfigurable computing and realtime embedded systems, as well as 3D computer vision and imaging. He has authored 5 refereed journal publications and more than 20 refereed conference publications, and has recently edited the Proceedings of the 2004 IEEE International Conference on Field Programmable Technology. He has been a member of the IEEE for eight years.     

Mobile geoinformation systems

The geoinformation system for handheld computers (PDAs) makes it possible to solve a wide range of geographically dispersed data (GDD) processing problems. The developed program software (PS) based on effective models and GDD processing methods has allowed significantly increasing the GDD processing rate in PDAs. Yurii G. Vasin was born in 1940 and graduated from Gor’kii State University in 1962. He received his doctoral (doctor of science) degree in 1988 and was a recipient of the Prize of the Council of Ministers of the USSR in 1990. He is the director of the Research Institute of Applied Mathematics and Cybernetics of the State University of Nizhni Novgorod. His scientific interests include theoretical and applied computer science, pattern recognition and image processing, and information technologies, and he is the author of more than 100 publications. Sergei V. Zherzdev was born in 1976 and graduated from the State University of Nizhni Novgorod in 1999. He is a software engineer at the Research Institute of Applied Mathematics and Cybernetics of the State University of Nizhni Novgorod. His scientific interests include theoretical and applied computer science and data compression techniques. He is the author of 7 publications. Andrei A. Egorov was born in 1982 and graduated from the State University of Nizhni Novgorod in 2006. He is a programmer at the Research Institute of Applied Mathematics and Cybernetics of the State University of Nizhni Novgorod, and his scientific interests include hierarchical structures of data storage on mobile platforms. He is the author of 2 inventions and 7 publications.     

Fast training for object recognition with structure-from-motion

In this paper we present a system for statistical object classification and localization that applies a simplified image acquisition process for the learning phase. Instead of using complex setups to take training images in known poses, which is very time-consuming and not possible for some objects, we use a handheld camera. The pose parameters of objects in all training frames that are necessary for creating the object models are determined using a structure-from-motion algorithm. The local feature vectors we use are derived from wavelet multiresolution analysis. We model the object area as a function of 3D transformations and introduce a background model. Experiments made on a real data set taken with a handheld camera with more than 2500 images show that it is possible to obtain good classification and localization rates using this fast image acquisition method. The text was submitted by the authors in English. Marcin Grzegorzek, born in 1977, obtained his Master’s Degree in Engineering from the Silesian University of Technology Gliwice (Poland) in 2002. Since December 2002 he has been a PhD candidate and member of the research staff of the Chair for Pattern Recognition at the University of Erlangen-Nuremberg, Germany. His fields are 3D object recognition, statistical modeling, and computer vision. He is an author or coauthor of seven publications. Michael Reinhold, born in 1969, obtained his degree in Electrical Engineering from RWTH Aachen University, Germany, in 1998. Later, he received a Doctor of Engineering from the University of Erlangen-Nuremberg, Germany, in 2003. His research interests are statistical modeling, object recognition, and computer vision. He is currently a development engineer at Rohde & Schwarz in Munich, Germany, where he works in the Center of Competence for Digital Signal Processing. He is an author or coauthor of 11 publications. Ingo Scholz, born in 1975, graduated in computer science at the University of Erlangen-Nuremberg, Germany, in 2000 with a degree in Engineering. Since 2001 he has been working as a research staff member at the Institute for Pattern Recognition of the University of Erlangen-Nuremberg. His main research focuses on the reconstruction of light field models, camera calibration techniques, and structure from motion. He is an author or coauthor of ten publications and member of the German Gesellschaft für Informatik (GI). Heinrich Niemann obtained his Electrical Engineering degree and Doctor of Engineering degree from Hannover Technical University, Germany. He worked with the Fraunhofer Institut für Informationsverarbeitung in Technik und Biologie, Karlsruhe, and with the Fachhochschule Giessen in the Department of Electrical Engineering. Since 1975 he has been a professor of computer science at the University of Erlangen-Nuremberg, where he was dean of the engineering faculty of the university from 1979 to 1981. From 1988 to 2000, he was head of the Knowledge Processing research group at the Bavarian Research Institute for Knowledge-Based Systems (FORWISS). Since 1998, he has been a spokesman for a “special research area” with the name of “Model-Based Analysis and Visualization of Complex Scenes and Sensor Data” funded by the German Research Foundation. His fields of research are speech and image understanding and the application of artificial intelligence techniques in these areas. He is on the editorial board of Signal Processing, Pattern Recognition Letters, Pattern Recognition and Image Analysis, and the Journal of Computing and Information Technology. He is an author or coauthor of seven books and about 400 journal and conference contributions, as well as editor or coeditor of 24 proceedings volumes and special issues. He is a member of DAGM, ISCA, EURASIP, GI, IEEE, and VDE and an IAPR fellow.     

Algorithmic and architectural design for real-time and power-efficient Retinex image/video processing

This paper presents novel algorithmic and architectural solutions for real-time and power-efficient enhancement of images and video sequences. A programmable class of Retinex-like filters, based on the separation of the illumination and reflectance components, is proposed. The dynamic range of the input image is controlled by applying a suitable non-linear function to the illumination, while the details are enhanced by processing the reflectance. An innovative spatially recursive rational filter is used to estimate the illumination. Moreover, to improve the visual quality results of two-branch Retinex operators when applied to videos, a novel three-branch technique is proposed which exploits both spatial and temporal filtering. Real-time implementation is obtained by designing an Application Specific Instruction-set Processor (ASIP). Optimizations are addressed at algorithmic and architectural levels. The former involves arithmetic accuracy definition and linearization of non-linear operators; the latter includes customized instruction set, dedicated memory structure, adapted pipeline, bypasses, custom address generator, and special looping structures. The ASIP is synthesized in standard-cells CMOS technology and its performances are compared to known Digital signal processor (DSP) implementations of real-time Retinex filters. As a result of the comparison, the proposed algorithmic/architectural design outperforms state-of-art Retinex-like operators achieving the best trade-off between power consumption, flexibility, and visual quality.

Program and research system for the recognition of individuals by photos of faces on documents

In this article, the developed program and research system for recognizing individuals based on photos of faces on documents is described. The requirements for the system made at the development stage are determined. The most important of these requirements is the possibility of carrying out the investigations of various algorithms with the purpose of the comparing their efficiency, determining their optimum parameters, and selecting the best system of signs. The composition and destination of the main components of the program and research system for recognizing individuals are presented. The main feature of implementation is the use of processing scenarios in the system performed by an interpreter and the presence of an expanded set of the elemental processing functions. This solution results in the rapid development and variation of various algorithms of image processing, formation of signs, and classification. Evgenii Valer’evich Myasnikov. Born in 1981. In 2004, he graduated the Samara State Aerospace University (SGAU) and entered the Post-Graduate Education of SGAU. In 2007, Myasnikov defended the Candidate of Science (Engineering) Dissertation. Currently, he works 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. Vladislav Viktorovich Sergeev. Born in 1951. In 1974, he graduated the Kuibyshev Aviation Institute (now, the Samara State Aerospace University). In 1994, he defended his Doctor of Science (Engineering) dissertation. Currently, he works at the Chief of Laboratory of Mathematical Methods of Image Processing at the Image Processing Systems Institute, Russian Academy of Sciences. The circle of scientific interests involves the digital processing of signals, analysis of images, pattern recognition, and geoinformatics. Sergeev has more than 200 publications, including about 40 articles and two monographs (in partnership). Sergeev is the Chairman of the Povolzh’e Division of the Russian Association of Pattern Recognition and Image Analysis. He is the Corresponding Member of the Russian Environmental Academy and Academy of the Engineering Sciences of the Russian Federation, the member of SPIE (the International Society for Optical Engineering), and the Laureate of the Samara Regional Prize in the Field of Science and Engineering. 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 Institute, Russian Academy of Sciences. The 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, including more than 30 articles and one monograph (in partnership). He is the member of the Russian Association of Pattern Recognition and Image Processing. Aleksandr Pavlovich Chikhonadskikh. Born in 1959. In 1981, he graduated the Mozhaiskii Military Space Engineering Institute (now, the Mozhaiskii Military Space Engineering Academy). In 1988, he defended the Candidate of Science (Engineering) Dissertation. Currently, he is working as the Chief of the Second Research Department at the FGUP State Research Institute of Applied Problems. The circle of scientific interests involves the creation of program-apparatus complexes, digital processing of signals, analysis of images, and pattern recognition. Chikhonadskikh has more than 70 publications, including three articles and three monographs (two in partnership). Aleksandr Viktorovich Koryakin. Born in 1959. In 1982, he graduated the Dnepropetrovsk State University. In 2002, he defended the Doctor of Science (Engineering) Dissertation. Currently, he is working as the Senior Researcher at the FGUP State Research Institute of Applied Problems. The circle of scientific interests involves the digital processing of signals, analysis of images, pattern recognition, and creation of software-apparatus complexes. Koryakin has more than 100 publications, including three monographs. Inga Yur’evna Terent’eva. Born in 1978. In 2000, she graduated the North-West Academy of State Service (St. Petersburg), and in 2004, she graduated the Post-Graduate Education at the Institute of the Human Brain, Russian Academy of Sciences. In 2005, she defended the Candidate of Science (Psychological) Dissertation. Currently, she is working as the Chief of Laboratory at the FGUP State Research Institute of Applied Problems. The circle of scientific interests involves the analysis of biometric data, pattern recognition, and neural networks. Terent’eva has 23 publications, including eight articles.     

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.     

Automatic updating of raster images of electronic charts

The technology being developed to ensure remote updating of raster images of electronic charts (EC) via global data transmission networks is considered. Implemented methods are presented that can automatically synchronize EC with minimal requirements for the channel capacity. The constructed version of the control system and similar general-purpose software are compared in terms of their efficiency in detecting the differences in graphic data for BIG images. Yurii G. Vasin was born in 1940 and graduated from Gorki State University in 1962. He received his doctoral (doctor of science) degree in 1988, is a member of the Russian Academy of Natural Sciences, and a recipient of the Prize of the Council of Ministers of the USSR in 1990. At present, he is the director of the Research Institute of Applied Mathematics and Cybernetics of the State University of Nizhni Novgorod. His scientific interests include theoretical and applied computer science, pattern recognition and image processing, and information technologies. He is the author of more than 100 publications. Sergei V. Zherzdev was born in 1976 and graduated from the State University of Nizhni Novgorod in 1999. At present, he is a postgraduate student at the same university and a software engineer at the Research Institute of Applied Mathematics and Cybernetics of the State University of Nizhni Novgorod. His scientific interests include theoretical and applied computer science and data compression techniques. He is the author of 7 publications. Evgenii S. Sorokin was born in 1985 and graduated from the Lobachevskii State University of Nizhni Novgorod from the Computational Mathematics and Cybernetics Department in 2007 and the Economics Department in 2008. At present, he is a postgraduate student at the Intellectual Information Systems and Geoinformatics Department. His scientific interests include applied computer science, geoinformation systems, and efficient data processing techniques. He is the author of 6 publications.     

Family of models for describing one class of metallographic images

Models for images syntax are developed, tried, and tested in describing the syntax of microstructural metallographic images of wrought aluminum alloys. Gennadii Mikhailovich Tsibul’skii was born in 1947 and graduated from Krasnoyarsk Polytechnic Institute in 1973. Since 1975, he has been involved in the analysis of digital images. In 1978, he completed his postgraduate course at the Lenin Leningrad Electronic Technical Institute. He received his candidate’s degree in 1987 and a doctoral degree in engineering in 2006. He was appointed a professor in 2007. In 1996, he founded the Artificial Intelligence Systems Department and has worked there as a chairman since then. His scientific interests include the multiagent approach to images analysis, and he is the author of more than 70 publications (including one book published by the Siberian Branch of the Russian Academy of Sciences). At present, Gennadii Tsibul’skii is the director of the Space and Information Technologies Institute at Krasnoyarsk Siberian Federal University. Yurii Anatol’evich Maglinest was born 1965 and graduated from Krasnoyarsk Polytechnic Institute in 1973; he then pursued postgraduate studies there. He received his candidate’s degree in engineering in 1996 in the analysis of metallographic images. He is an associate professor at the State Commission for Academic Degrees and Titles of the Russian Federation. At present, he is a chair of the Scientific University Laboratory of Flexible Software Systems at the Artificial Intelligence Systems Department at Krasnoyarsk Siberian Federal University. His scientific interests include aerospace information storage, processing and analysis, and flexible software systems. Dmitrii Al’bertovich Perfil’ev was born in 1968 and graduated from Krasnoyarsk Polytechnic Institute in 1992. Since 2000, he has been specializing in problems in digital images analysis and, in particular, in describing microstructural pictures of aluminum alloys. He received his candidate’s degree in engineering in 2007 and is the author of 8 publications related to the problem in question. At present, he is a researcher and a lecturer at the Artificial Intelligence Systems Department at Krasnoyarsk Siberian Federal University.     

ASIP-based reconfigurable architectures for power-efficient and real-time image/video processing

To meet both flexibility and performance requirements, particularly when implementing high-end real-time image/video processing algorithms, the paper proposes to combine the application specific instruction-set processor (ASIP) paradigm with the reconfigurable hardware one. As case studies, the design of partially reconfigurable ASIP (r-ASIP) architectures is presented for two classes of algorithms with widespread diffusion in image/video processing: motion estimation and retinex filtering. Design optimizations are addressed at both algorithmic and architectural levels. Special processor concepts used to trade-off performance versus flexibility and to enable new features of post-fabrication configurability are shown. Silicon implementation results are compared to known ASIC, DSP or reconfigurable designs; the proposed r-ASIPs stand for their better performance–flexibility figures in the respective algorithmic class.

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.     

QoS Management Through Adaptive Reservations

Reservation based (RB) scheduling is a class of scheduling algorithms that is well-suited for a large class of soft real-time applications. They are based on a bandwidth abstraction, meaning that a task is given the illusion of executing on a dedicated slower processor. In this context, a crucial design issue is deciding the bandwidth that each task should receive. The point we advocate is that, in presence of large fluctuations on the computation requirements of the tasks, it can be a beneficial choice to dynamically adapt the bandwidth based on QoS measurements and on the subsequent application of feedback control (adaptive reservations).In this paper, we present two novel contributions to this research area. First, we propose three new control algorithms inspired to the ideas of stochastic control. Second, we present a flexible and modular software architecture for adaptive reservations. An important feature of this architecture is that it is realised by means of a minimally invasive set of modifications to the Linux kernel.This work has been partially supported by the European OCERA IST-2001-35102 and RECSYS IST-2001-32515 projects.Luca Abeni is a Ph.D. in Computer Engineering at the Scuola Superiore SantAnna of Pisa (Italy). He graduated in Computer Engineering at the University of Pisa in 1998, and received a Ph.D. in Computer Engineering at the Scuola SuperioreS. Anna of Pisa in 2002. During 2000 he was a visiting student at the Carnegie Mellon University (Pittsburgh, PA), working with Prof. Ragunathan Rajkumar on resource reservation algorithms for real-time kernels. During 2001 he was a visiting student a Oregon Graduate Institute (Portland, OR) working with Prof. Jonathan Walpole on the support for time-sensitive applications in the Linux kernel. He has been working in Broadsat S.R.L. since 2003, developing audio/video streaming solutions and IPTV applications.Tommaso Cucinotta got the degree in Computer Engineering at the University of Pisa (Italy) in 2000. He got the Ph.D. inComputer Engineering at the Scuola Superiore SantAnna(SSSA) of Pisa in 2004 with a thesis titled Issues in authentication by means of smart-card devices. He held a course on cryptography in the International Master on Software Engineering organized at SSSA in 2002 and 2004. At the moment, he cooperates in research activities at the Scuola Superiore S. Anna in the areas of computer security and Quality of Service control for soft real-time systems.Giuseppe Lipari graduated in Computer Engineering at the University of Pisa in 1996, and received the Ph.D. degree in Computer Engineering from Scuola Superiore SantAnna in 2000. During 1999, he was avisiting student at University of North Carolina at Chapel Hill, collaborating with professor S.K. Baruah and professor K. Jeffay on real-time scheduling. Currently, he is assistant professor of Operating Systems with Scuola Superiore SantAnna. His main research activities are in real-time scheduling theory and its application to real-time operating systems, soft real-time systems for multimedia applications and component-based real-time systems.Luca Marzario is a Ph.D. student in Computer Engineering at the Scuola Superiore S. Anna of Pisa, Italy. In 2002, he graduated in Computer Engineering at University of Pisa. His main research interest include real-time systems scheduling, aperiodic service mechanism, feedback-scheduling, QoS in multimedia systems, Linux kernel and Real Time Linux executives (RTAI, RTLinux).Luigi Palopoli graduated in Control Engineering at the University of Pisa in 1998 and received his Ph.D. degree in Computer Engineering in 2002 from the Scuola Superiore S. Anna, Pisa. During 2001 he was a visiting scholar at the Department of EECS, University of California at Berkeley, where he worked on design techniques for real-time controllers under the supervision of Professor Alberto Sangiovanni-Vincentelli. He is currently Assistant Professor at the Scuola Superiore S. Anna (Pisa). His main research activities include Quality of Service control, control of systems under communication and computation constraints and design of embedded systems.     

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.     

Facial expression recognition based on Haar-like feature detection

In this paper we propose a novel approach for facial feature detection in color image sequences using Haar-like classifiers. The feature extraction is initialized without manual input and has the capability to fulfill the real time requirement. For facial expression recognition, we use geometrical measurement and simple texture analysis in detecting facial regions based on the prior detected facial feature points. For expression classification we used a three layer feed forward artificial neural network. The efficiency of the suggested approach is demonstrated under real world conditions. The text was submitted by the authors in English. Axel Panning was born in Magdeburg, Germany, in 1980. He received his Masters Degree (Dipl.-Ing.) in Computer Science at the University of Magdeburg, Germany, in 2006. He is currently working on a PhD thesis focusing on image processing, tracking, and pattern recognition. Ayoub K. Al-Hamadi was born in Yemen in 1970. He received his Masters Degree (Dipl.-Ing.) in Electrical Engineering and Information Technology in 1997 and his PhD in Technical Computer Science at the Ottovon-Guericke-University of Magdeburg, Germany, in 2001. Since 2002 he has been Assistant Professor and Junior-Research-Group-Leader at the Institute for Electronics, Signal Processing, and Communications at the Otto-von-Guericke-University Magdeburg. His research work concentrates on the field of image processing, tracking analysis, pattern recognition, and artificial neural networks. Dr. Al-Hamadi is the author of more than 60 articles. Robert Niese was born in Halberstadt, Germany, in 1977. He received his Masters Degree (Dipl.-Ing.) with distinction in computer science at the Otto-von-Guericke-University Magdeburg, Germany, in 2004. He gathered broad experience in several international internship investigations on medical image and data analysis, including MRI, CT, and EEG. He is currently working at Magdeburg University on his PhD thesis, which focuses on 3D, image processing, tracking, and pattern recognition. Robert Niese is the author of more than 15 publications. 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 200 papers.     

A Simple Robotic System for Neurorehabilitation

In the recent past, several researchers have shown that important variables in relearning motor skills and in changing the underlying neural architecture after stroke are the quantity, duration, content, and intensity of training sessions. Unfortunately, when traditional therapy is provided in a hospital or rehabilitation center, the patient is usually seen for few hours a week. Robot-mediated therapies could improve this situation but even if interesting results have been achieved by several groups, the use of robot-mediated therapy has not become very common in clinical practice. This is due to many different reasons (e.g., the “technophobia” of some clinicians, the need for more extensive clinical trials) but one of the more important is the cost and the complexity of these devices which make them difficult to be purchased and used in all the clinical centers. The aim of this work was to verify the possibility of improving motor recovery of hemiparetic subjects by using a simple mechatronic system. To achieve this goal, our system (named “MEchatronic system for MOtor recovery after Stroke” (MEMOS)) has been designed with the aim of using mainly “off-the-shelf products” with only few parts simply manufactured with standard technology, when commercial parts were not available. Moreover, the prototype has been developed taking into account the requirements related to the clinical applicability such as robustness and safety. The MEMOSsystem has been used during clinical trials with subjects affected by chronic hemiparesis (<6 months from the cerebrovascular accident). The results obtained during these experiments seem to showthat notwithstanding the simple mechatronic structure characterizing theMEMOSsystem, it is able to help chronic hemiparetics to reduce their level of impairment. Further clinical experiments with acute and chronic subjects will be carried out in order to confirm these preliminary findings. Moreover, experiments for tele-rehabilitation of patients will be also carried out. Silvestro Micera was born in Taranto, Italy, on August 31, 1972. He received the University degree (Laurea) in electrical engineering from the University of Pisa, Pisa, Italy, in 1996, and the Ph.D. degree in biomedical engineering from the Scuola Superiore Sant'Anna, Pisa, Italy, in 2000. From 1998 to 2001, he was the Project Manager of the EU GRIP Project (ESPRIT LTR Project 26322, “An integrated system for the neuroelectrIic control of grasp in disabled persons”). During 1999, he was a Visiting Researcher at the Center for Sensory-Motor Interaction, Aalborg University. Since May 2000, he has been an Assistant Professor of Biomechanical Engineering at the Scuola Superiore Sant'Anna. He is currently involved in several projects on neuro-robotics and rehabilitation engineering. His research interests include the development of neuro-robotic systems (interfacing the central and peripheral nervous system with robotic artefacts) and the development of mechatronic and robotic systems for function restoration in disabled persons. Dr. Micera is an Associate Editor of the IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING and member of the IEEE Engineering in Medicine and Biology and Robotics and Automation Societies. M. Chiara Carrozza received the Laurea degree in physics from the University of Pisa, Pisa, Italy, in 1990. Since 2001, she has been an Associate Professor of biomedical robotics at the Scuola Superiore Sant'Anna, Pisa, Italy. She is the co-cordinator of the Advanced Robotics Technology and Systems Laboratory where she is responsible for some national and international projects in the fields of biorobotics. Her research interests are in the fields of biorobotics (artificial hands, upper limb exoskeletons), rehabilitation engineering (neurorehabilitation, domotic, and robotic aids), and biomedical microengineering (microsensors, tactile sensors). She is an author of several scientific papers and international patents. Eugenio Guglielmelli received the Laurea degree and the PhD in electronics engineering from the University of Pisa, Italy, in 1991 and in 1995, respectively. He is currently Associate Professor of Bioengineering at Campus Bio-Medico University in Rome, Italy, where he teaches the courses of Bio-Mechatronics and of Rehabilitation Bioengineering, and where he also recently co-founded the new Research Laboratory of Biomedical Robotics & Electro-Magnetic Compatibility. He has been working in the field of biomedical robotics over the last fifteen years at Scuola Superiore Sant'Anna where he also served from 2002 to 2004 as the Head of the Advanced Robotics Technology & Systems Laboratory (ARTS Lab), founded by prof. Paolo Dario in 1991. His main current research interests are in the fields of novel theoretical and experimental approaches to human-centered robotics and to biomporphic control of mechatronic systems, and in their application to robot-mediated motor therapy, assistive robotics, neuro-robotics and neuro-developmental engineering. He serves in the Editorial Board of the International Journal on Applied Bionics and Biomechanics. He has been Guest Co-Editor of the Special Issue on Rehabilitation Robotics of the International Journal ‘Autonomous Robots’. He is member of the IEEE Robotics & Automation Society, of the IEEE Engineering in Medicine & Biology Society, of the Society for Neuroscience, and of the Association for the Advancement of Assistive Technology in Europe (AAATE). He served (2002–03) as the Secretary of the IEEE Robotics & Automation Society (RAS) and he is currently Co-chair of the RAS Technical Committee on Rehabilitation Robotics. He serves in the Programme Committees of several International Conferences, such as ICRA, IROS, ICAR, AIM, BIOROB and others. He was/is a member of the Organizing Committees of ICAR2003, IROS2004, IFAC/SYROCO2006 and ICRA2007. Giovanni Cappiello received the M.E. degree from the University of Pisa, Pisa, Italy. He is currently working towards the Ph.D. degree in robotics at the ARTS Lab of the Scuola Superiore Sant'Anna Pisa. He worked on the RTR IV Prosthetic Hand Project. Among his research interests are rehabilitation technologies, biomedical and surgical devices, osseointegration, and biomimetic artificial sensors. He is involved in the design of antropomorphic hands and arm and in the exploitation of compliant joints. Franco Zaccone was born in Policoro, Italy. He received the University degree (Laurea) in electrical engineering from the University of Pisa, Pisa, Italy, in 2000. Since June 2000, he has been a Research Assistant at the Advanced Robotics Technologies and Systems Laboratory, Scuola Superiore Sant'Anna, Pisa. His research interests include the design of hardware systems for rehabilitation engineering and motion analysis. Cinzia Freschi was born in Caserta, Italy, on December 25, 1969. She received the University degree (Laurea) in computer engineering from the University of Pisa, Pisa, Italy, in 1998. Since 1998, she has been research assistant at the Advanced Robotics Technology and Systems Laboratory (ARTSLAB), Scuola Superiore Sant'Anna. Her research interests are in the filed of rehabilitation engineering and neuro-robotics. Roberto Colombo received the Dr. Eng. degree in electrical engineering from the Politecnico of Milano, Milan, Italy, in 1980. Since 1981, he has been a Research Engineer in the Bioengineering Department of the “Salvatore Maugeri” Foundation, IRCCS, Rehabilitation Institute, Veruno, Italy. From 1998 to 2001, he was a Partner of the European Community project “Prevention of muscular disorders in operation of computer input devices (PROCID).” From 2001 to 2004, he was the Coordinator of the project “Tecniche robotizzate per la valutazione ed il trattamento riabilitativo delle disabilitá motorie dell'arto superiore,” 2001-175, funded by the Italian Ministry of Health. His research interests include robot-aided neurorehabilitation, muscle tone and spasticity evaluation, muscle force and fatigue assessment, speech production mechanisms study, cardiovascular control assessment by spectral analysis of heart rate variability signals, and respiratory mechanics assessment. He has taught several national courses in the field of neurorehabilitation. He is the author of over 20 papers and the co-editor of one book on the subject of speech production mechanisms. Alessandra Mazzone received the degree (Diploma) in computer science, from the ITIS “Leonardo da Vinci,” Borgomanero, Italy, in 1988. Since 1989, she has been a Programmer at the Bioengineering Department, the Fondazione Salvatore Maugeri, Rehabilitation Institute of Veruno (NO), Italy. Her research interests include robot-aided neurorehabilitation, cardiovascular control assessment by spectral analysis of heart rate variability signals, and respiratory mechanics assessment. Carmen Delconte received the Diploma in neurophysiology techniques from the University of Pavia, Pavia, Italy, in 1989. She is currently with the Clinical Neurophysiology Unit, Scientific Institute of Veruno “Salvatore Maugeri” Foundation, Rehabilitation Institute, Veruno, Italy. Her research concerns the quantification of muscle tone, emg-biomechanical studies, and the robotic rehabilitation of upper limb in cerebrovascular diseases. She has been published in the clinical and electrophisiological field of neuromuscular diseases and on the topic of stroke patients rehabilitation. Her current research is focused on the evaluation and treatment of upper limbs disorders like spasticity and paresis. Dr. Delconte is a member of the Italian Neurophysiology Technician Society. Fabrizio Pisano received the M.D. degree from the University of Milan, Milan, Italy, in 1981. In 1986, he completed his training as resident in neurology and became Neurologist at the same University He was a teacher in “Electromyography” from 1991 to 1997 at the School of Physical Medicine and Rehabilitation, the University of Turin, Torino, Italy. He has taught several national and international electromyographic courses on hand neuromotor rehabilitation, occupational pathology, rehabilitation therapy, muscle fatigue, posture and movement, clinical neurophysiology, and EMG Culture. He was a Scientific Project co-leader of a telethon program (1994–1996); speech motor control in ALS; a search for an early marker of disease. He was the Project Leader of “Quantitative Analysis of Spastic Hypertonia” by the Istituto Superiore della Sanitá during 1998–1999. He was the Clinical Scientific Leader of the INAIL project “International clinical survey over functional electrical stimulation.” He was the Scientific Project Leader of the Clinical Neurophysiology Unit of the project “Tecniche robotizzate per la valutazione ed il trattamento riabilitativo delle disabilitá motorie dell'arto superiore,” 2001-175, funded by the Italian Ministry of Health. He is currently a Neurologist and the Head of the Clinical Neurophysiology Unit, ”Salvatore Maugeri” Foundation, IRCCS, Rehabilitation Institute, Veruno, Italy. He has been published in the clinical and electrophysiological field of neuromuscular diseases and on the topic of stroke patients rehabilitation. His current research interests are in evaluation and treatment of upper limb disorders like spasticity and paresis. Dr. Pisano is a Member of the Italian Neurological Society and the Italian Clinical Neurophysiology Society. Giuseppe Minuco received the Dr. Eng. degree in mechanical engineering from the Politecnico Milano, Milan, Italy, in 1972, and a postgraduate degree in biomedical engineering from the Faculty of Medicine, Bologna, Italy, in 1975. He is currently Head of the Bioengineering Department, “Salvatore Maugeri” Foundation, IRCCS, Pavia, Italy. He is Chair of the Technical Scientific Committee of “CBIM” (Medical Informatics and Bioengineering Consortium) Pavia, Italy. He is Member of the Editorial Board of The Monaldi Archives for Chest Disease and of Giornale Italiano di Medicina del Lavoro ed Ergonomia. Has taught several courses in healthcare management. His main interests are in the fields of rehabilitation engineering, clinical engineering, medical informatics, and telemedicine. Paolo Dario received the Dr. Eng. degree in mechanical engineering from the University of Pisa, Pisa, Italy, in 1977. He is currently a Professor of Biomedical Robotics at the Scuola Superiore Sant'Anna, Pisa, Italy. He also teaches courses at the School of Engineering of the University of Pisa, and at the Campus Biomedico University, Rome, Italy. He has been a Visiting Professor at Brown University, Providence, RI, at the Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland, and at Waseda University, Tokyo, Japan. He was the founder of the Advanced Robotics Technologies and Systems (ARTS) Laboratory and is currently the co-cordinator of the Center for Research in Microengineering (CRIM) Laboratory of the Scuola Superiore Sant'Anna, where he supervises a team of about 70 researchers and Ph.D. students. He is also the Director of the Polo Sant'Anna Valdera and a Vice-Director of the Scuola Superiore Sant'Anna. His main research interests are in the fields of medical robotics, mechatronics, and micro/nanoengineering, and specifically in sensors and actuators for the above applications. He is the coordinator of many national and European projects, the editor of two books on the subject of robotics, and the author of more than 200 scientific papers (75 in ISI journals). He is Editor-in-Chief, Associate Editor, and Member of the Editorial Board of many international journals. Prof. Dario served as President of the IEEE Robotics and Automation Society during 2002–2003, and he is currently Co-Chair of the Technical Committees on Bio-robotics and of Robo-ethics of the same society. He is a Fellow of the European Society on Medical and Biological Engineering, and a recipient of many honors and awards, such as the Joseph Engelberger Award. He is also a Member of the Board of the International Foundation of Robotics Research (IFRR).     

On minimizing errors in 3D reconstruction for stereo camera systems

Active reconstruction of 3D surfaces deals with the control of camer a viewpoints to minimize error and uncertainty in the reconstructed shape of an object. In this paper we develop a mathematical relationship between the setup and focal lengths of a stereo camera system and the corresponding error in 3D reconstruction of a given surface. We explicitly model the noise in the image plane, which can be interpreted as pixel noise or as uncertainty in the localization of corresponding point features. The results can be used to plan sensor positioning, e.g., using information theoretic concepts for optimal sensor data selection. The text was submitted by the authors in English. Stefan Wenhardt, born in 1978, graduated in mathematics at the University of Applied Sciences, Regensburg, Germany, in 2002, with a degree of Dipl.-Math. (FH). Since June 2002, he has been a research staff member at the Chair for Pattern Recognition at the Friedrich-Alexander-University of Erlangen-Nuremberg, Germany. The topics of his research are 3D reconstruction and active vision systems. He is author or coauthor of four publications. Joachim Denzler, born April 16, 1967, received a degree of Diplom-Informatiker, Dr.-Ing. and Habilitation from the University of Erlangen in 1992, 1997, and 2003, respectively. Currently, he holds a position of a full professor for computer science and is head of the computer vision group, Faculty of Mathematics and Informatics, University of Jena. His research interests comprise active computer vision, object recognition and tracking, 3D reconstruction, and plenoptic modeling, as well as computer vision for autonomous systems. He is author and coauthor of over 80 journal papers and technical articles. He is member of the IEEE computer society, DAGM, and GI. For his work on object tracking, plenoptic modeling, and active object recognition and state estimation, he was awarded with the DAGM best paper awards in 1996, 1999, and 2001, respectively. Heinrich Niemann obtained the degree of Dipl.-Ing. in Electrical Engineering and Dr.-Ing. from Technical University Hannover, Germany. He worked at the Fraunhofer Institut fur Informationsverarbeitung in Technik und Biologie, Karlsruhe, and at Fachhochschule Giessen in the department of Electrical Engineering. Since 1975 he has been Professor of Computer Science at the University of Erlangen-Nurnberg, where he was dean of the engineering faculty of the university from 1979–1981. From 1988–2000 he was head of the research group Knowledge Processing at the Bavarian Research Institute for Knowledge-based Systems (FORWISS). Since 1998 he has been the speaker of a special research area entitled Model-based Analysis and Visualization of Complex Scenes and Sensor Data, which is funded by the German Research Foundation (DFG). His fields of research are speech and image understanding and the application of artificial intelligence techniques in these fields. He is on the editorial boards of Signal Processing, Pattern Recognition Letters, Pattern Recognition and Image Analysis, and Journal of Computing and Information Technology. He is the author or coauthor of 7 books and about 400 journal and conference contributions, as well as editor or coeditor of 24 volumes of proceedings and special issues. He is a member of DAGM, ISCA, EURASIP, GI, and IEEE, and a Fellow of IAPR.     

Neural network based biometric personal identification with fast iris segmentation

This paper presents the iris recognition system for biometric personal identification using neural network. Personal identification consists of localization of the iris region and generation of a data set of iris images followed by iris pattern recognition. In this paper, a fast algorithm is proposed for the localization of the inner and outer boundaries of the iris region. Located iris is extracted from an eye image, and, after normalization and enhancement, it is represented by a data set. Using this data set a Neural Network (NN) is used for the classification of iris patterns. The adaptive learning strategy is applied for training of the NN. The results of simulations illustrate the effectiveness of the neural system in personal identification. Recommended by Guest Editor Phill Kyu Rhee. This work was supported by the Near East University. The authors would like to thank Institute of Automation, Chinese Academy of Sciences for providing CASIA iris database. Rahib Hidayat Abiyev was born in Azerbaijan, in 1966. He received the Ph.D. degree in Electrical and Electronic Engineering from Azerbaijan State Oil Academy (old USSR) in 1997. He worked as a Research Assistant at the research laboratory “Industrial intellectual control systems” of Computer-aided control system department. From 1999-present he is working as an Associate Professor at the department of Computer Engineering of Near East University. He is the Chairman of Computer Engineering Department. His research interests are softcomputing, pattern recognition, control systems, signal processing, optimization. Koray Altunkaya was born in Turkey, in 1982. He received the MSc. degree in Computer Engineering from Near East University, North Cyprus in 2007. He is working as an Research Assistant at the research laboratory “Applied Computational Intelligence” of Computer Engineering Department. His research interests are image processing, neural networks, pattern recognition, digital signal processing.     

Nonparametric pattern recognition systems based on learning a sample decomposition by its dimension

The technique of multilevel nonparametric pattern recognition systems synthesis on the basis of learning sample decomposition principles and parallel computing technology is proposed. This basis provides effective processing of highly dimensional information. Aleksandr Vasil’evich Lapko was born in 1949 and graduated from Frunze Polytechnic Institute in 1971. He has been a doctor of technical sciences since 1990 and a leading researcher at the Institute of Computational Modeling of the Siberian Branch of the Russian Academy of Sciences. His scientific interests include the following: nonparametric statistics, pattern recognition systems, and the design and optimization of indefinite systems. He is the author of 223 publications, including 13 monographs. He is chairman of the Krasnoyarsk regional department of the Pattern Recognition and Image Analysis Association and an Honored Science Worker of the Russian Federation. Vasilii Aleksandrovich Lapko was born in 1974 and graduated from Krasnoyarsk State Technical University in 1996. He has been a doctor of technical sciences since 2004 in systems analysis, management, and information processing. He is a senior researcher at the Institute of Computational Modeling of the Siberian Branch of the Russian Academy of Sciences. His scientific interests include the following: nonparametric statistics, pattern recognition systems, the design of indefinite systems, and collective evaluation methods. He is the author of 105 publications, including 4 monographs. He was awarded by the Russia Academy of Sciences a medal for the best scientific publication in 2005 for young scientists in Informatics, Computer Engineering, and Automation.     

Universal method for controlling maximum error in image compression

A method for controlling the maximum restoration error in image compression is proposed that can be used in combination with the arbitrary methods of compression. The method has been studied for the case of its application together with the standard compression method JPEG. The results have shown that, at equal coefficients of compression, the proposed method substantially reduces the maximum error of image restoration. Sergeev Vladislav Viktorovich. Was born in 1951, in 1974 got his degree from the Kuybyshev Aircraft Institute (now the State Aerospace University of Samara). In 1993 he defended his dissertation to the degree of the Doctor of Technical Sciences. At present he is the Head of the Laboratory of Mathematical Methods of Image Processing at the Institute of the Systems of Image Processing of the Russian Academy of Sciences. The circle of his research interests includes digital processing of signals, analysis of images, pattern recognition, geoinformatics. He has over 200 publications, including about 40 papers, two monographs (in collaboration). He is Chairman of the Volga Division of the Russian Association of Pattern Recognition and Image Analysis. He is a Corresponding Member of the Russian Ecological Academy and the Academy of Engineering Sciences of the RF, a member of the SPIE (International Society for Optical Engineering), prize winner of the Samara Administration Prize in Science and Technology. Timbay Yelena Ivanovna. Was born in 1985. In 2008 got her degree from the Samara State Aerospace University (SSAU). At present she is a technician at the Institute of the Image Processing Systems, RAS. She is engaged in image processing, imag compression. Has 11 publication, including 3 articles.