PATTERN RECOGNITION FEATURE AND IMAGE PROCESSING THEORY ON THE BASIS OF STOCHASTIC GEOMETRY
Nikolay G. Fedotov, Lyudmila A. Shulga, Alexander V. Moiseev, Andrey S. Kol’chugin
2005
Abstract
Application of stochastic geometry methods to pattern recognition is analysed. The paper is based on Trace-transformations of original images into images on the Möbius band. Based on the new geometric transformation, a new approach towards the construction of features, independent of images’ motions or their linear transformations, is put forward. A prominent characteristics of the group of features under consideration is that we can represent each of them as a consecutive composition of three functionals. The paper considers the application of three-functional structure of recognition feature to image pre-processing. Feature can be invariant or sensitive to the group of all motions transformation and linear deformation of objects depending of functionals selection. Thus sensitive features are suitable to determine the parameters of translation. It is an important task for robotics.
References
- Fedotov N.G., 1990. Metody Stokhasticheskoi Geometrii v Raspoznavanii Obrazov (Methods of Stochastic Geometry in Patters Recognition), Moscow, Radio i Svjaz.
- Fedotov N.G., Kadyrov A.A., 1995. Image scanning in machine vision leads to new understanding of image. In Proc. of 5th International Workshop on Digital In Processing and Computer Graphics, Proc. International Society for Optical Engineering (SPIE), Vol. 2363, pp. 256-261.
- Helgason S., 1980. The Radon Transform, Birkhauser, Basel and Boston, Massachusetts.
- Fedotov N.G., Shulga L.A., 2000. New Theory of Pattern Recognition on the Basis of Stochastic Geometry. In WSCG'2000 Conference Proceedings, Vol. 1, ?. 373- 380.
- Fedotov N.G., Shulga L.A., 2004. Feature Generation and Stochastic Geometry. In Proc. of the 4th International Workshop on Pattern Recognition in Information Systems, PRIS'2004, Porto, Portugal, p. 169-175.
- Fedotov N.G., Shul'ga L.A., Roy A.V., 2005. Visual Mining for Biometrical System Based on Stochastic Geometry Pattern Recognition and Image Analysis, Vol. 15, No. 2, 2005, pp. 389-392.
- Fedotov N.G., Nikiforova T.V., 2002. Technical defectoscopy based on new pattern recognition theory, Izmeritel'naya tekhnika (Measurement technics), 2002, No. 12, pp. 27-31.
Paper Citation
in Harvard Style
G. Fedotov N., A. Shulga L., V. Moiseev A. and S. Kol’chugin A. (2005). PATTERN RECOGNITION FEATURE AND IMAGE PROCESSING THEORY ON THE BASIS OF STOCHASTIC GEOMETRY . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO, ISBN 972-8865-30-9, pages 187-192. DOI: 10.5220/0001160601870192
in Bibtex Style
@conference{icinco05,
author={Nikolay G. Fedotov and Lyudmila A. Shulga and Alexander V. Moiseev and Andrey S. Kol’chugin},
title={PATTERN RECOGNITION FEATURE AND IMAGE PROCESSING THEORY ON THE BASIS OF STOCHASTIC GEOMETRY},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,},
year={2005},
pages={187-192},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001160601870192},
isbn={972-8865-30-9},
}
in EndNote Style
TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,
TI - PATTERN RECOGNITION FEATURE AND IMAGE PROCESSING THEORY ON THE BASIS OF STOCHASTIC GEOMETRY
SN - 972-8865-30-9
AU - G. Fedotov N.
AU - A. Shulga L.
AU - V. Moiseev A.
AU - S. Kol’chugin A.
PY - 2005
SP - 187
EP - 192
DO - 10.5220/0001160601870192