Abstract
In this work, four alternative algorithms for Classification/ Discrimination are described which we have developed recently. These are believed to have several advantages over the previous ones via the introduction of a new concept, Centers of Masses for classes, and new cost functions which enforce clustering of different classes more explicitly compared to the previous approaches.
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.
Similar content being viewed by others
References
Duda, R., Hart, P.: Pattern Classification and Scene Analysis. Wiley, Chichester (1973)
Reisfeld, D., Wolf son, H., Yeshurun, Y.: Context free attentional operators: the generalized symmetry transform. Int. J. of Computer Vision, Special Issue on Qualitative Vision 14, 119–130 (1995)
Kumar, B., Casasent, D., Murakami, H.: Principal component imagery for statistical pattern recognition correlators. Optical Engineering 21(1) (1982)
Wilks, S.S.: Mathematical Statistics. John Wiley and Sons, Inc., Chichester (1962)
Moghaddam, B.: Probabilistic visual learning for object detection. In: The 5th International Conference on Computer Vision, Cambridge, MA (June 1995)
Cover, M., Thomas, J.A.: Elements of Information Theory. John Wiley and Sons, New York (1994)
Belhumeur, P., Hespanha, J.: Eigenfaces vs. Fisherfaces: Recognition Using Class Specifica Linear Projection. IEEE Trans. Pattern Analysis and Machine Intelligence 19(7), 711–720 (1997)
Cui, Y., Swets, D., Weng, J.: Learning-based hand sign recognition using SHOSLIF- M. In: Int’l Conf. on Computer Vision, pp. 631–636 (1995)
Woodham, R.J.: Analysing images of curved surfaces. Artificial Intelligence 17, 117–140 (1981)
Karson, M.J.: Multivariate Statistical Methods. The Iowa Univ. Press (1982)
Watanabe, S.: Pattern Recognition: Human and Mechanical (1985)
Hand, D.J.: Construction and Assessment of Classification Rules. John Wiley and Sons, Chichester (1997)
Roberts, S.J., Husmeier, D., Rezek, L.: Bayesian approaches to Gaussian mixture modeling. IEEE Trans. Pattern Recognition and Machine Intelligence 20(11) (November 1998)
Raudys, S.: On dimensionality, sample size, and classification error of nonparametric linear classification algorithms. IEEE Trans. Pattern Recognition and Machine Intelligence 19(6) (June 1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Demirkol, A., Demir, Z., Emre, E. (2006). Alternative Approaches and Algorithms for Classification. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2006. Lecture Notes in Computer Science, vol 4142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11867661_4
Download citation
DOI: https://doi.org/10.1007/11867661_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44894-5
Online ISBN: 978-3-540-44896-9
eBook Packages: Computer ScienceComputer Science (R0)