Scope
Automation of image mining is one of the most important strategic goals in image analysis, recognition and understanding science and technologies. The main subgoals are developing and applying of mathematical theory for constructing image models accepted by efficient pattern recognition algorithms and for standardized representation and selection of image analysis transforms.

Taking as a strategic goal the automated image mining it is necessary to provide image analysis professionals and final users with the following opportunities:
. automated design, test and adaptation of techniques and algorithms for image recognition, estimation and understanding;
. automated selection of techniques and algorithms for image recognition, estimation and understanding;
. automated testing of the raw data quality and suitability for solving the image recognition problem;
. standard technological schemes for image recognition, estimation, understanding and retrieval.

Automation of image-mining is possible by complex application techniques for image analysis, understanding and 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 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 and physical nature and 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, reproduction and rendering, and mathematical, computational and technological means allowable for the IAE.

We may consider that the main contradiction is related to the "pictorial nature" of an image and the "formal" (symbolic) foundations of IAE: it is well known that to take an advantage from data representation an image form is necessary to reduce the latter to a "non-image" form.

In IAE is used a wide spectrum of mathematical techniques from algebra, geometry, discrete mathematics, mathematical logics, probability theory, mathematical statistics, calculus, as well as the techniques of mathematical theory of pattern recognition, digital signal processing, and physics (in particular, optics).

The mathematical theory of image analysis is not finished and is passing through a developing stage. It is only recently came understanding of the fact 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 natural way to overcome the above mentioned contradiction between "pictorial nature" of an image and the "formal" (symbolic) foundations of IAE is to introduce pattern recognition oriented image models and necessary means and techniques for reduction of an image to a recognizable form without loss of image specificity. The careful study of the challenge revealed the opportunity to solve it via a theory establishing reasonable ties between an image nature, IAE applications, pattern recognition philosophy, image representations and models, IAE transforms, and corresponding information technologies.

The purpose of the workshop is 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.

The workshop will be organized in cooperation with the Technical Committee No. 16 "Algebraic and Discrete Mathematical Techniques in Pattern Recognition and Image Analysis" of the International Association for Pattern Recognition. The workshop will consist of a small number of invited talks, contributed talks, and informal discussions, and a wrap-up session. The workshop will begin with an opening session to introduce the workshop topics, goals, participants, and expected outcomes. The invited talks will give overviews of the key topics. Contributed talks (selected based on review by at least two members of the program committee), will represent a mix of new results based on completed work, work in progress, research challenges, and applications.

Given the increasing interest on this subject, the current call for papers is intended to offer the possibility to discuss the most recent advances in the area.

Topics of interest include, but are not limited to:
1. New Mathematical Techniques in Image Mining:
. Algebraic Approaches
. Discrete Mathematics Techniques
. Structural and Syntactic Techniques
. Multiple Classifiers
. Other Mathematical Techniques
2. Image Models and Image Features
3. Automation of Image Mining:
. Image Mining, Computer Vision and Knowledge-Based Systems
. Image Databases
. Image Knowledge Bases
. Image Mining Technologies
. Linguistic Tools:
o Image Science Ontologies;
o Image Science Thesauri.
4. Applied Problems

Workshop Program Committee
Sergey Ablameyko, Belarusian Association for Image Analysis & Recognition, Byelorus Republik
Goesta H. Granlund, Linkoping University, Linkoping, Sweden
Heikki Kalviainen, Lappeenranta University of Technology, Lappeenranta, Finland
Valeriy Kirichuk, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russian Federation
Josef Kittler, University of Surrey, Guildford, United Kingdom
Anatoly Nemirko, St. Petersburg Electrotechnical University "LETI", St. Petersburg, Russian Federation
Yury Obukhov, Institute for Radioengineering and Electronics of the RAS, Moscow, Russian Federation
Jussi Parkkinen, University of Joensuu, Finland
Igor Persiantsev, Research Institute for Nuclear Physics, Moscow Lomonosov State University, Moscow, Russian Federation
Bernd Radig, Technical University of Munich, Munich, Germany
Gerhard Ritter, University of Florida, Gainesville, FL, USA
Vladimir Ryazanov, Dorodnicyn Computing Center of the Russian Academy of Sciences, Moscow, Russian Federation
Jose Ruiz-Shulcloper, the Advanced Technologies Applications Center, Cuba
Tieniu Tan, National Pattern Recognition Laboratory, Beijing, China
Yury Vasin, Nizhny Novgorod Lobachevsky State University, Nizhny Novgorod, Russian Federation
Patrick S. P. Wang, Northeastern University, USA
Nicolai Zagorujko, Institute of Mathematics of the SB of the RAS, Novosibirsk, Russian Federation
Yuri Zhuravlev, Dorodnicyn Computing Center of the Russian Academy of Sciences, Moscow, Russian Federation

Workshop Proceedings
All accepted and registered papers will be published in a workshop proceedings book with an ISBN reference, which will be issued by INSTICC Press. The proceedings will be available at the time of the workshop. There will be also a CD-ROM publication. A selection of the best selected papers will be considered for improvement and publication in a special issue of Image and Vision Computing Journal. Full revised texts of all papers presented at the workshop will be published in the special issue of the international journal "Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications" (MAIK "Nauka/Interperiodica" (Moscow) Pleiades Publishing distributed worldwide by SPRINGER), 2008.