Alexander B. Blinov Tula State University Lenin Ave. 92, 300600 Tula Russia Phone: (087-2) 35-36-37 FAX: (087-2) 33-13-05 E-mail: blinov@atm.tsu.tula.ru ba070867@uic.tula.ru

Academic History:

1996

Ph.D. degree, Institute of Control Problems of the Russian Academy of Sciences, Moscow.

Thesis: Segmentation Algorithms for Composite Texture Images.

1990

M.S. degree, Tula Polytechnic Institute, Department of Electronic Computing Machines.

Scientific History:

Since 1996

Associate Professor,
Tula State University, Department of Technical Cybernetics.

Lecture Courses: Methods of Optimization, Theory and Technology of Computer Programming, Informatics, Theory of Calculation Processes and Structures.

Theoretical Research: Pattern recognition in signals and data fields with changing probabilistic properties, Markov methods for signal and image analysis.

Applications: Analysis of seismic explorative data arrays, computer telephony, image analysis.

1993-1996

Assistant Professor,
Tula State University, Department of Technical Cybernetics.

Lecture Courses: Methods of Optimization

Research: Methods and algorithms of massive data set processing based on models of random processes and fields with changing probabilistic properties.

Applications: Analysis of seismic explorative data arrays, image analysis.

1993-1990

Teaching Assistant and Graduate Student,
Tula State University, Department of Technical Cybernetics.

Subjects: Probability Theory, Computer Programming, Theory of Automatic Control.

Research: Models of random processes and fields with changing probabilistic properties.

Scientific Interests:

Models of random processes and fields with changing probabilistic properties, change detection in random processes and fields, pattern recognition in signal and image analysis, image segmentation, texture analysis, stereo image analysis, analysis of geophysical exploratory data.

Publications:

About 20 scientific publications.

Some papers in English:

Blinov, A.B, Michailov A.Yu. Segmentation of composite texture images on hidden Markov models of lines. Abstract of communication Sixth International Vilnius Conference on Probability Theory and Mathematical Statistics, Vilnius, June 28 - July 3, 1993.

Mottl V.V., Blinov A.B., Kopylov A.V., Zheltov S.Yu. Quasi-statistical approach to the problem of stereo image matching. SPIE Proceedings, 1994, Vol. 2363, pp. 50- 61.

V.V. Mottl, A.B. Blinov. A texture processing algorithm and its application to seismic section segmentation. The 4th Open Russian German Workshop “Pattern Recognition and Image Analysis”. Valday, Russian Federation, March 3-9, 1996, pp. 103-106.

V.V. Mottl, A.B. Blinov, A.V. Kopylov. Generalized technique for a class of image analysis problems based on tree-like quasi-Markov models of the hidden information. The 4th Open Russian German Workshop “Pattern Recognition and Image Analysis”. Valday, Russian Federation, March 3-9, 1996, pp. 107-111.

V.V. Mottl, A.B. Blinov, A.V., Kostin. Algorithms for analysis of three-dimensional textures and their application to processing the data of seismic prospecting. Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications, 1996, Vol. 6, № 2.

Mottl V.V., Muchnik I.B., Blinov A.B., Kopylov A.V. Hidden Tree-Like Quasi-Markov Model and Generalized Technique for a Class of Image Processing Problems. 13th International Conference on Pattern Recognition. Vienna, Austria, August 25-29, 1996. Track B, pp. 715-719.

V.V. Mottl, A.B. Blinov, A.V., Kostin. Texture analysis algorithms and their application to seismic data processing Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications, 1997, Vol. 7, № 1

Mottl V.V., Muchnik I.B., Blinov A.B., Kopylov A.V. A generalized approach to a class of image processing problems based on a tree-like quasi-Markov model of neighborhood between the grid elements Pattern Recognition and Image Analysis. Advances in Mathematical Theory and Applications, 1997, Vol. 7, № 1

V.V. Mottl, A.B. Blinov, A.V. Kopylov, A.A. Kostin. Optimization techniques on pixel neighborhood graphs for image processing Graph-Based Representations in Pattern Recognition (J.-M. Jolion and W.G. Kropatsch, ed.). Computing, Supplement 12. Springer-Verlag/Wien, 1998, pp. 135-145.

V.V. Mottl, A.B. Blinov, A.V. Kopylov, A.A. Kostin, I.B. Muchnik. Variational methods in signal and image analysis. Proceedings of the 14th International Conference on Pattern Recognition. Brisbane, Australia, August 16-20, 1998. Volume I, pp. 525-527.