Email this article REDUCTION OF COMPUTATIONAL COSTS FOR IDENTIFICATION OF THE PATCHLOCATION ON LARGE-SIZED IMAGES
- Authors: Tashlinskii AG1, Kaveev IN1, Khoreva AM1
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- Issue: Vol 8, No 3 (2010)
- Pages: 73-76
- Section: Articles
- URL: https://journals.eco-vector.com/2073-3909/article/view/55836
- ID: 55836
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Abstract
The use of the pseudo-gradient method for solving the problems of pattern search, identification and parameter estimation of image patch location is proposed. At that the reference and sought image patches may have relative spatial and brightness deformations. The structural optimization of search algorithms is used for computational costs reduction. The expressions for calculation of the image patch erroneous choice probability and the probability distribution of the offered algorithms iteration number are found.
About the authors
A G Tashlinskii
Email: tag@ulstu.ru
I N Kaveev
Email: k.ibragim@gmail.com
A M Khoreva
References
- Huang T.S., Netravali T.S. 3-D motion estimation // Machine Vision for Tree-Dimensional Scenes. New York: Academic, 1990. - Р. 194-219.
- Tomasi С., Kanade T. Shape and Motion from Image Streams Under Orthography // A Factorization Method, Int'l J. Computer Vision. V. 9, N. 2, 1992. - Р. 137154.
- Jacobson L., Wechsler H. Derivation of optical flow using a spatiotemporal-frequency approach // Comput. Vision, Graphics. Image Processing. V. 38, 1987. - Р. 29-65.
- Soille P. Morphological Image Analysis. Berlin, Heidelberg; New York: Springer-Verlag, 1993. - 420 р.
- Rajala S.A., Abdelqader I. M., BilbroG. L., Synder W. E. Motion estimation optimization // IEEE Proc. ICASSP-92, V 3, 1992. - Р. 226-236.
- Wang Y. and Lee O. Active mesh - A feature seeking and tracking image sequence representation scheme // IEEE Trails. Image Processing. V. 3, 1994. - Р. 610624.
- Цыпкин Я.З. Информационная теория иден-тификации. М.: Наука. Физматлит, 1995. - 520 с.
- Tashlinskii A.G. Pseudogradient Estimation of Digital Images Interframe Geometrical Deformations // Vision Systems: Segmentation & Pattern Recognition. Vienna, Austria: I-Tech Education and Publishing, 2007. - Р. 465-494.
- Поляк Б.Т., Цыпкин Я.З. Псевдоградиентные алгоритмы адаптации и обучения // Автоматика и телемеханика. №3, 1973. - С. 45-68.
- Ташлинский А.Г., Тихонов В.О. Методика анализа погрешности псевдоградиентного измерения параметров многомерных процессов // Известия вузов: Радиоэлектроника. Т. 44, № 9, 2001. - С. 7580.
- Tashlinskii A. Computational Expenditure Reduction in Pseudo-Gradient Image Parameter Estimation // Computational Science-ICCS 2003. V. 2658, Proceeding, Part II, Berlin: Springer, 2003. - Р. 456462.
- Tashlinskii A.G., Muratkhanov D.S. Structural Optimization of Pseudogradient Algorithms for Measuring Interframe Image Deformations // Pattern Recognition and Image Analysis. 2003, V.13, N.1, 2003. - Р. 177-178.
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