Abstract
A distribution p X|K : X × K → ℝ at of conditional probabilities of observations x ∈ X, under the condition that the object is in a state k ∈ K, is the central concept on which various task in pattern recognition are based. Now is an appropriate time to introduce examples of conditional probabilities of observations with the help of which we can elucidate the previous as well as the following theoretical construction. In this lecture we will stop progressing in the main direction of our course for a while to introduce the two simplest functions p X|K which are the most often used models of the recognised object.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Bibliographical notes
Duda, R. and Hart, P. (1973). Pattern classification and scene analysis. John Willey and Sons, New York.
Devijver, P. and Kittler, J. (1982). Pattern recognition: A statistical approach. Prentice-Hall, Englewood Cliffs, NJ.
Fukunaga, K. (1990). Introduction to statistical pattern recognition. Academic Press, Boston, 2nd edition.
Levenstein, V. (1965). Dvojichnyje kody s ispravlenijem vypadenij, vstavok i zameshchenij simvolov; in Russian (Binary coded correcting deletions, insertions and replaces of symbols). Doklady Akademii nauk SSSR, 163 (4): 840–850.
Anderson, T. (1958). An introduction to multivariate statistical analysis. John Wiley, New York, USA.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Schlesinger, M.I., Hlaváč, V. (2002). Two statistical models of the recognised object. In: Ten Lectures on Statistical and Structural Pattern Recognition. Computational Imaging and Vision, vol 24. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-3217-8_3
Download citation
DOI: https://doi.org/10.1007/978-94-017-3217-8_3
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-6027-3
Online ISBN: 978-94-017-3217-8
eBook Packages: Springer Book Archive