In conjunction with the 8th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - VISIGRAPP 2013
SCOPE
Automation of image mining is one of the most important strategic goals in image analysis, recognition and understanding both in scientific and technological aspects. The main subgoals are developing and applying of mathematical theory for constructing image models and representations accepted by efficient pattern recognition algorithms and for constructing standardized representation and selection of image analysis transforms. Automation of image-mining is possible by combined application of mathematical theory of image analysis/understanding/recognition and mathematical theory of pattern recognition.
Automation of image processing, analysis, estimating and understanding is one of the crucial points of theoretical computer science having decisive importance for applications, in particular, for diversification of solvable problem types and for increasing the efficiency of problem solving.
The role of an image as an analysis and estimation object is determined by its specific and inalienable informational properties. Image is a mixture and a combination of initial (raw, “real”) data and its representation means, of computational procedures and of the physical nature and of the models of objects, events and processes to be represented via an image.
The specificity, complexity and difficulties of image analysis and estimation (IAE) problems stem from necessity to achieve some balance between such highly contradictory factors as goals and tasks of a problem solving, the nature of visual perception, ways and means of an image acquisition, formation, representation, reproduction and rendering, and mathematical, computational and technological means allowable for the IAE.
The mathematical theory of image analysis is not finished and is passing through a developing stage. It appeared not so long ago that only intensive creating of comprehensive mathematical theory of image analysis and recognition (in addition to the mathematical theory of pattern recognition) could bring a real opportunity to solve efficiently application problems via extracting from images the information necessary for intellectual decision making. The transition to practical, reliable and efficient automation of image-mining is directly dependent on introducing and developing of mathematical means for IAE.
The participants will enjoy the opportunity to discuss a methodology, mathematical and computational techniques for automation of image mining on the base of mathematical theory for IAE. Another important task of the workshop is to discuss linguistic tools for image mining – image knowledge bases and image science ontologies – and to estimate the prospects of the algebraic approach in representation of image analysis knowledge in this environment. The interpretation of mathematical and linguistic techniques will be illustrated by application problems, mainly from biology and medicine, automation of scientific research, and many other domains generating breakthrough and difficult application tasks.
This workshop is intended to cover, but it is not limited to, the following topics:
1. New Mathematical Techniques in Image Mining
• Algebraic Approaches
• Discrete Mathematics Techniques
• Descriptive Techniques and Data Representation Problems
• Structural and Syntactic Techniques
• Multiple Classifiers
• Pattern Recognition Techniques in Image-Mining Environment
• Other Mathematical Techniques
• Machine Learning
2. Image Models, Representations and Features
3. Automation of Image Mining
• Image Mining, Computer Vision and Knowledge-Based Systems
• Image Databases
• Image Knowledge Bases
• Image Mining Technologies
• Biomedical Image Mining
• Knowledge Representation and Linguistic Tools
o Image Science Ontologies
o Image Science Thesauri
4. Applied Problems
Workshop Program Committee
Professor Dr.
Sergey Ablameyko, Belarusian State University, Minsk, Belarus
Professor Dr.
Eduardo Bayro Corrochano, CINVESTAV Unidad Guadalajara, México
Professor Dr.
Joachim Denzler, Friedrich-Schiller University of Jena, Germany
Professor Dr.
Gennady Emelyanov, Yaroslav-the-Wise Novgorod State University, Veliky Novgorod, Russian Federation
Professor Dr.
Heikki Kalviainen, Lappeenranta University of Technology, Finland
Professor Dr.
Mikhail Khachay, Institute of Mathematics and Mechanics, Ural Branch of the RAS, Ekaterinburg, Russian Federation
Professor Dr.
Valeriy Kirichuk, Institute of Automation and Electrometry, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russian Federation
Professor Dr.
Josef Kittler, University of Surrey, Guildford, United Kingdom
Professor Dr.
Vladimir Mazurov, Ural State University, Ekaterinburg, Russian Federation
Professor Dr.
Gerard Medioni, Institute for Robotics and Intelligence Systems, University of Southern California, Los Angeles, CA, USA
Dr.
Eckart Michaelsen, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation, Ettlingen, Germany
Professor Dr.
Anatoly Nemirko, St. Petersburg Electrotechnical University "LETI", St. Petersburg, Russian Federation
Dr.
Yury Obukhov, Kotel'nikov Institute of Radio Engineering and Electronics, Russian Academy of Sciences, Moscow, Russian Federation
Professor Dr.
Jussi Parkkinen, University of Eastern Finland, Joensuu, Finland
Professor Dr.
Dietrich Paulus, University of Koblenz, Germany
Professor Dr.
Igor Persiantsev, Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russian Federation
Professor Dr.
Bernd Radig, Technical University of Munich, Munich, Germany
Professor Dr.
Gerhard Ritter, University of Florida, Gainesville, FL, USA
Dr.
Vladimir Ryazanov, Dorodnicyn Computing Center, Russian Academy of Sciences, Moscow, Russian Federation
Professor Dr.
Sudeep Sarkar, University of South Florida, Tampa, FL, USA
Dr.
Oleg Sen'ko, Dorodnicyn Computing Center, Russian Academy of Sciences, Moscow, Russian Federation
Professor Dr.
Jose Ruiz Shulcloper, Advanced Technologies Application Center (CENATAV), Cuba, Cuba
Professor Dr.
Ching Y. Suen, Concordia University, Montreal, Quebec, Canada
Professor Dr.
Tieniu Tan, National Pattern Recognition Laboratory, Beijing, China
Professor Dr.
Yuri Vasin, Research Institute for Applied Mathematics and Cybernetics, Lobachevsky State University of Nizhni Novgorod, Nizhni Novgorod, Russian Federation
Professor Dr.
Yuri Zhuravlev, Dorodnicyn Computing Centre, Russian Academy of Sciences, Moscow, Russian Federation