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

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Transcranial Doppler detection and monitoring of cerebral microemboli have provided a new and useful method to diagnose, and potentially to foresee, increased risk of stroke. Until now, however, the assessment of this method in routine clinical practice has been limited by the lack of a reliable automatic differentiation between solid and gaseous microemboli. The aim of this work is the definition of a clinical diagnostic support procedure for the automatic recognition of emboli of different composition. The proposed method makes use of image processing techniques and neural algorithms for data interpretation and performs a feature-based analysis of the ultrasonographic images showing the microembolic events. Application to clinical cases selected by expert neurologists for their clinical relevance and experimental results have showed effective operability of the developed procedure. The text was submitted by the authors in English. Sara Colantonio, MS honors degree in Computer Science from the University of Pisa in 2004, PhD student in information engineering at the Dept. of Information Engineering, University of Pisa, is a research fellow at the Institute of Information Science and Technologies of the Italian National Research Council, in Pisa. She has a grant from Finmeccanica for studies in the field of image categorization with applications in medicine and quality control. Her main interests include neural networks, machine learning, industrial diagnostics, and medical imaging. She is coauthor of more than fifteen scientific papers. At present, she is involved in a number of European research projects regarding image mining, information technology, and medical decision support systems. Ovidio Salvetti, director of research at the Institute of information science and Technologies (ISTI) of the Italian National Research Council (CNR), in Pisa, is working in the field of theoretical and applied computer vision. His fields of research are image analysis and understanding, pictorial information systems, spatial modeling, and intelligent processes in computer vision. He is coauthor of four books and monographs and more than three hundred technical and scientific articles; he is also owner of ten patents regarding systems and software tools for image processing. He has been scientific coordinator of several national and European research and industrial projects in the fields of computer vision and high-performance computing for diagnostic imaging. He is member of the editorial boards of the international journals Pattern Recognition and Image Analysis and G. Ronchi Foundation Acts. He is at present the CNR contact person in ERCIM (the European Research Consortium for Informatics and Mathematics) for the Working Group on “Vision and Image Understanding,” member of IEEE and of the steering committee of a number of EU projects. He is head of the ISTI Signals and Images Laboratory.  相似文献   

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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.  相似文献   

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Left Ventricle (LV) Ejection Fraction (EF) is a fundamental parameter for heart function assessment. Being based on border tracing, however, manual computation of EF is time-consuming and extremely prone to inter-and intraobserver variability. In this paper we present an automatic method for EF computation which provides results in agreement with those provided by expert observers. The segmentation strategy consists of two stages: first, the region of interest is identified by means of mimetic criteria; then, the identified region is used for initialization of an active contour based on a variational formulation of level set methods, which provides accurate segmentation of the LV cavity. Volume calculation is then performed according to the conventional Simpson’s rule and, finally, the EF is computed. The text was submitted by the authors in English. Umberto Barcaro is an Associate Professor at the Computer Science Department of Pisa University and an Associate Researcher at the Signals and Images Laboratory of the Institute of Information Science and Technologies of the National Research Council. He teaches Physics and Computer Science Laboratory at the Faculty of Pharmacy, and Signal Theory at the Faculty of Sciences. His research activity regards the automatic analysis of signals and images of clinical interest. In particular, he has studied spontaneous and evoked electroencephalographic and polygraphic signals, and ultrasound images. Davide Moroni (Magenta, 1977), M.Sc. in Mathematics honours degree from the University of Pisa in 2001, dipl. at the Scuola Normale Superiore of Pisa in 2002, PhD in Mathematics at the University of Rome “La Sapienza” in 2006, is a research fellow at the Institute of Information Science and Technologies of the Italian National Research Council, in Pisa. His main interests include geometric modeling, computational topology, image processing and medical imaging. At present he is involved in a number of European research projects working in discrete geometry and dynamic scene analysis. Ovidio Salvetti, director of research at the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council (CNR), in Pisa, is working in the field of theoretical and applied computer vision. His fields of research are image analysis and understanding, pictorial information systems, spatial modeling, and intelligent processes in computer vision. He is a coauthor of four books and monographs and more than three hundred technical and scientific articles; he also possesses ten patents regarding systems and software tools for image processing. He has been a scientific coordinator of several national and European research and industrial projects, in collaboration with Italian and foreign research groups, in the fields of computer vision and high-performance computing for diagnostic imaging. He is member of the editorial boards of the international journals Pattern Recognition and Image Analysis and G. Ronchi Foundation Acts. He is at present the CNR contact person in ERCIM (the European Research Consortium for Informatics and Mathematics) for the Working Group on Vision and Image Understanding, member of IEEE and of the steering committee of a number of EU projects. He is head of the ISTI Signals and Images Laboratory.  相似文献   

11.
A fast method for computing Hu’s image moment invariants is described. The invariants are found by approximation using generalized moments computed in a sliding window by a parallel recursive algorithm. The proposed method is shown to be computationally more efficient than direct computation. Vladislav V. Sergeev. Born 1951. Graduated from the Kuibyshev Aviation Institute (now, the Samara State Aerospace University) in 1974. Received doctoral degree (Dr. Sc. (Eng.)) in 1993. Head of Laboratory of Mathematical Methods of Image Processing, Image Processing Systems Institute, Russian Academy of Sciences. Scientific interests: digital signal processing, image analysis, pattern recognition, and geoinformatics. Author of more than 150 publications, including about 40 papers in journals, and a co-author of 2 monographs. Chair of the Volga-region Branch of the Russian Federation Association for Pattern Recognition and Image Analysis. Corresponding Member of the Russian Ecological Academy and the Russian Academy of Engineering, member of SPIE (The International Society for Optical Engineering), a winner of the Samara District Award for Science and Engineering. Ol’ga A. Titova. Born 1980. Graduated from the Samara State Aerospace University (SSAU) in 2002. Currently post-graduate student at the Chair of Geoinformatics, SSAU. Scientific interests: image analysis, pattern recognition, fast algorithms of digital image processing, and geoinformatics. Author of nine publications including three papers in journals. Member of the Russian Federation Association for Pattern Recognition and Image Analysis.  相似文献   

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Application of nonlinear methods of multivariate regression approximation (neural networks, functions linear in fitting parameters, and hierarchical approximation) is considered to problems of image filtering based on a priori information in the form of matched pairs of images (“ideal” and “degraded”). The methods are compared with regard to their efficiency. Vasilii N. Kopenkov. Born 1978. Graduated from the Samara State Aerospace University (SSAU) in 2001. Assistant Professor at the Chair of Geoinformatics, SSAU, and a Junior Researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing and pattern recognition. Author of four papers. Member of the Russian Federation Association for Pattern Recognition and Image Analysis. Andrei V. Chernov. Born 1975. Graduated from the Samara State Aerospace University (SSAU) in 1998. Received candidate’s degree (Cand. Sc. (Eng.)) in 2004. Assistant Professor at the Chair of Geoinformatics, SSAU, and a Researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing, pattern recognition, and geoinformation systems. Author of more than 50 publications, including 11 papers in journals, and a co-author of a monograph. Member of the Russian Federation Association for Pattern Recognition and Image Analysis. Vladislav V. Sergeev. Born 1951. Graduated from the Kuibyshev Aviation Institute (now, the Samara State Aerospace University). Received doctoral degree (Dr. Sc. (Eng.)) in 1993. Head of Laboratory of Mathematical Methods of Image Processing, Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: digital signal processing, image analysis, pattern recognition, and geoinformatics. Author of more than 150 publications, including about 40 papers in journals, and a co-author of 2 monographs. Chair of the Volga-region Branch of the Russian Federation Association for Pattern Recognition and Image Analysis. Corresponding Member of the Russian Ecological Academy and the Russian Academy of Engineering, member of SPIE (The International Society for Optical Engineering), a winner of the Samara District Award for Science and Engineering.  相似文献   

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We consider the purpose, functionality, configuration, and structure of a software environment designed for simulation and investigation of methods, algorithms, and information technology for digital images analysis and processing. Mikhail V. Gashnikov. Born 1975. Graduated from the Samara State Airspace University (SSAU) in 1998. Received candidate’s degree in Technology in 2004. He is now an assistant professor at the chair of earth information of the SSAU. Scientific interests: image processing, compression, statistical coding. Author of more than 30 publications, including 12 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis. Evgenii V. Myasnikov. Born 1981. Graduated from the Samara State Airspace University in 2004. He is now a post-graduate student at the Chair of Earth Information of the Samara State Airspace University. Scientific interests: development of software systems, image processing, image retrieval in databases. Author of 6 publications, including one paper. Member of the Russian Association for Pattern Recognition and Image Analysis. Andrei V. Chernov. Born 1975. Graduated from the Samara State Airspace University (SSAU) in 1998. Received candidate’s degree in Technology in 2004. He is now an assistant professor at the Chair of Earth Information of the SSAU and a research fellow at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing, pattern recognition, geoinformation systems. Author of more than 50 publications, including 11 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis. Nikolai I. Glumov. Born 1962. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1985. Received candidate’s degree in Technology in 1994. He is now a senior researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing and pattern recognition, compression of images, simulation of systems of digital image formation. Author of more than 50 publications, including 21 papers and one monographs (in coauthorsip). Member of the Russian Association for Pattern Recognition and Image Analysis. Vladislav V. Sergeev. Born 1951. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1974. Received doctoral degree in Technology in 1993. Head of the Laboratory of Mathematical Methods for Image Processing at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: digital signal processing, image analysis, pattern recognition, earth information. Author of more than 150 publications, including approximately 40 papers and two monographs (in coauthorship). President of the Povolzh’e Branch of the Russian Association for Pattern Recognition and Image Analysis. Corresponding member of the Russian Ecological Academy and of the Russian Academy of Engineering Sciences. Member of the International Society for Optical Engineering. A laureate of the Samara Provincial Government prize in science and engineering. Marina A. Chicheva. Born 1964. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1987. Received candidate’s degree in Technology in 1998. She is now a senior researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image recognition, compression, fast algorithms for discrete transformations. Author of more than 40 publications, including 15 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis.  相似文献   

14.
An image processing procedure is proposed aiming at detecting porosity defects in materials used in the aerospace industry by means of the analysis of C-scan images obtained by ultrasound inspection techniques. An image is described through a number of features, which are then analyzed in order to evaluate the similarity of an unknown examined image with respect to a set of reference ones. The procedure is performed by firstly applying a 2D wavelet transform of the input image and then a feature extraction process based on statistics of the detail images produced by the transform itself. A data reduction process is then applied using the principal component analysis technique. Finally, a decision ruler performs the image classification by considering the distance among points in the principal component plane. An application of this procedure is presented for the analysis of single images, giving a localization of defects. Preliminary results, obtained by processing both simulation images and real C-scan maps, showed the efficacy of the proposed method. The text was submitted by the authors in English. Edoardo Bozzi (Pisa, 1943) is a researcher at ISTI-CNR, in Pisa, working in the field of signal processing. His main interests include design of hardware and software instrumentation and development of noninvasive diagnostic techniques for medical and industrial applications. He is author of about a hundred technical papers. Maria Grazia Di Bono (Potenza, 1975), MS (2002) in computer science from the University of Pisa, has been performing since March 2003 her research activity at ISTI-CNR, in Pisa, working in the field of computer vision. Her main interests include neural networks, multimedia processing, and web systems for industrial and medical applications. She is coauthor of more than twelve technical and scientific papers. G. Cavaccini. Born in Naples October 28, 1959. Graduate in physics. From 1986 to 1988, he was at the Naples Section of the National Institute for Nuclear Physics, where he participated in research on gamma spectroscopy. From 1988 to 1999, he was at Aerodynamics Institute U. Nobile of the University of Naples with a scholarship on “Nondestructive Testing of Aeronautical Structures by Means of Thermographics Techniques.” From 1989 to the present date, he has been an Alenia Aeronautica employee. Up to 2001, he worked as an NDI technologist and researcher at the Engineering Materials, Processes, and NDI Dept. He holds ASNT Level III, Italian Aerospace NDT Board, and JAR 145 NDT certifications. He is involved also as coordinator in national and European research programs; since 2001, he has been responsible for nondestructive testing and structural health monitoring, as well as for the exploitation of technology research. Massimo Chimenti (Altopascio, 1946) is a senior scientist at ISTI-CNR, in Pisa, working in the field of signal and image formation, acquisition, and preprocessing. His scientific interests range from hardware design to software systems with specific applications in medical imaging. He is author of more than two hundred technical and scientific papers and he is also owner of more than ten patents regarding hardware and software systems for image acquisition and processing. He is at present leader of a research group in the Signals and Images Lab of ISTI working in the field of microwave and ultrasound imaging. Ovidio Salvetti, Director of Research at the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council (CNR), in Pisa, is working in the field of theoretical and applied computer vision. His fields of research are image analysis and understanding, pictorial information systems, spatial modeling, and intelligent processes in computer vision. He is coauthor of four books and monographs and more than three hundred technical and scientific articles; he is also owner of ten patents regarding systems and software tools for image processing. He has been scientific coordinator of several national and European research and industrial projects, in collaboration with Italian and foreign research groups, in the fields of computer vision and high-performance computing for diagnostic imaging. He is member of the editorial boards of the international journals Pattern Recognition and Image Analysis and G. Ronchi Foundation Acts. He is at present the CNR contact person in ERCIM (the European Research Consortium for Informatics and Mathematics) for the Working Group on “Vision and Image Understanding,” member of IEEE and of the steering committee of a number of EU projects. He is head of the ISTI Signals and Images Laboratory.  相似文献   

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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.  相似文献   

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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.  相似文献   

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The task of detection and tracking of a moving object is addressed. Algorithms have been developed which perform this task for monitoring and surveillance purposes. Prediction is also implemented in the algorithm to locate the target in order to keep it stationary in the center of the image, resolve events of occlusion or masking, and increase normal tracking performance. Real-time implementation generates deformation in target appearance, and then a shape database is used to improve these situations when a target is lost. A prototypical system has been developed that makes use of a moving camera located on a robotized system. A case study is presented about animal tracking in infrared live video. The text was submitted by the authors in English. Gabriele Pieri (Pescia, 1974), M. Sci. (2000) in Computer Science from the University of Pisa, since 2001 joined the “Signals and Images” Laboratory at ISTI-CNR, Pisa, working in the field of image analysis. His main interests include neural networks, machine learning, industrial diagnostics, and medical imaging. He is the author of more than 20 papers. Marco Benvenuti, born in 1965. He received a degree in electronic engineering from the University of Florence in 1994. Since 2002 he is director of the Research and Development Department of TD Group Spa. Since 1994 he has been a researcher and consultant of the National Research Council of Italy and he collaborates with various private and public research institutions, charged as scientifically responsible of several national and international research projects. His fields of activity are related to data and image processing and integration for environmental monitoring and analysis, satellite and airborne remote sensing techniques, and GIS applications. He has long experience in international projects management and was reviewer of the EU Commission as an expert on remote sensing and GIS applications. He has been a consultant to certain international organizations, such as the World Meteorological Organisation, F.A.O., and the European Space Agency. In 1996 he was the Italian delegate to the Thematic Cooperation Group on Operational Environment Monitoring of the DG-XII (EC). He has publications and communications at the national and international level. Edoardo Carnier, born in 1962. He received a degree in computer science from the University of Pisa in 1997, developing a thesis on high order perceptron initialization. He has strong experience in image processing and analysis. He participated in the design and development of the SIRIO infrared system for environmental monitoring and, in particular, contributed to the study and implementation of tracking and motion detection algorithms. Since February 1998 he has been on the staff of the research and development group of TD Group Spa as project manager on a research project to realize an integrated system based on infrared technology for video-surveillance applications. Ovidio Salvetti, Director of Research at the Institute of Information Science and Technologies (ISTI) of the Italian National research Council (CNR), in Pisa, is working in the field of theoretical and applied computer vision. His fields of research are image analysis and understanding, pictorial information systems, spatial modeling and intelligent processes in computer vision. He is co-author of four books and monographs and more than three hundreds technical and scientific articles; he is also owner of ten patents regarding systems and software tools for image processing. He has been scientific coordinator of several National and European research and industrial projects, in collaboration with Italian and foreign research groups, in the fields of computer vision and high-performance computing for diagnostic imaging. He is member of the Editorial Boards of the International Journals Pattern Recognition and Image Analysis and G. Ronchi Foundation Acts. He is at present the CNR Contact Person in ERCIM (the European Research Consortium for Informatics and Mathematics) for the Working Group on “Vision and Image Understanding,” Member of IEEE and of the Steering Committee of a number of EU Projects. He is Head of the ISTI “Signals and Images” Laboratory.  相似文献   

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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.  相似文献   

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Constrained frequent patterns and closed frequent patterns are two paradigms aimed at reducing the set of extracted patterns to a smaller, more interesting, subset. Although a lot of work has been done with both these paradigms, there is still confusion around the mining problem obtained by joining closed and constrained frequent patterns in a unique framework. In this paper, we shed light on this problem by providing a formal definition and a thorough characterisation. We also study computational issues and show how to combine the most recent results in both paradigms, providing a very efficient algorithm that exploits the two requirements (satisfying constraints and being closed) together at mining time in order to reduce the computation as much as possible. Francesco Bonchi received his Ph.D. in computer science from the University of Pisa in December 2003, with the thesis “Frequent Pattern Queries: Language and Optimizations”. Currently, he is a postdoc at the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council in Pisa, where he is a member of the Knowledge Discovery and Delivery Laboratory. He has been a visiting fellow at the Kanwal Rekhi School of Information Technology, Indian Institute of Technology, Bombay (2000, 2001). His current research interests are data mining query language and Optimization, frequent pattern mining, privacy-preserving data mining, bioinformatics. He is one of the teachers of a course on data mining held at the faculty of Economics at the University of Pisa. He served as a referee at various national and international conferences on databases, data mining, logic programming and artificial intelligence. Claudio Lucchese received the Master Degree in Computer Science summa cum laude from Ca' Foscari University of Venice in October 2003. He is currently a Ph.D. student at the same university and Research Associate at the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council in Pisa, where he is a member of the High Performance Computing Laboratory. He is mainly interested in frequent pattern mining, privacy-preserving data mining, and data mining techniques for information retrieval.  相似文献   

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