Stable Feature Extraction with the Help of Stochastic Information Measure
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6744)
This article discusses the problem of extraction of such set of pattern features that is informative and stable with respect of stochastic noise. This is done through the stochastic information measure.
KeywordsAdditive Measure Information Measure Stochastic Noise Discrete Curve Stochastic Measure
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
- 1.Bronevich, A., Lepskiy, A.: Geometrical Fuzzy Measures in Image Processing and Pattern Recognition. In: Proc. of the 10th IFSA World Congress, Istanbul, Turkey, pp. 151–154 (2003)Google Scholar
- 2.Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification and Scene Analysis: Part I Pattern Classification. John Wiley and Sons, Chichester (1998)Google Scholar
- 4.Lepskiy, A.E.: Application of Stochastic Information Measure in Problem of Finding of Optimal Polygonal Curve Representation. In: Proc. of Intern. Conf. Pattern Recognition and Image Analysis, Nizhni Novgorod, vol. 1, pp. 397–400 (2008)Google Scholar
- 5.Shiryaev, A.N.: Probability (Graduate Texts in Mathematics). Springer, Heidelberg (1995)Google Scholar
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