Summary
This paper is addressing problems related to the construction of classifiers in which the typical vector representation of a pattern is replaced with matrix data. We introduce some new variants of the method based on the Similarity Discriminant Function (SDF). The algorithms were tested on images of handwritten digits and on the photographs of human faces. On the basis of the experiments we can state that our modifications improved the performance of the SDF classifier.
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.
References
Turk, M., Pentland, A.: Eigenfaces for Recognition. J. Cognitive Neuroscience 3(1), 71–86 (1990)
Cheng, Y.-Q., Liu, K., Yang, J.-Y.: A Novel Feature Extraction Method for Image Recognition Based on Similar Discriminant Function (SDF). Pattern Recognition 26(1), 115–125 (1993)
Cheng, Y.-Q., Zhuang, Y.-M., Yang, J.-Y.: Optimal Fisher Discriminant Analysis Using the Rank Decomposition. Pattern Recognition 25(1), 101–111 (1992)
Samaria, F., Harter, A.: Parameterisation of a Stochastic Model for Human Face Identification. In: Proc. 2nd IEEE Workshop on Applications of Computer Vision (1994)
Garris, M.D., Wilkinson, R.A.: NIST Special Database 3. Handwritten Segmented Characters. National Institute of Standard and Technology, Gaithesburg, MD, USA (1992)
Okada, T., Tomita, S.: An Optimal Orthonormal System for Discriminant Analysis. Pattern Recognition 18(2), 139–144 (1985)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Smiatacz, M., Malina, W. (2009). New Variants of the SDF Classifier. In: Kurzynski, M., Wozniak, M. (eds) Computer Recognition Systems 3. Advances in Intelligent and Soft Computing, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93905-4_25
Download citation
DOI: https://doi.org/10.1007/978-3-540-93905-4_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-93904-7
Online ISBN: 978-3-540-93905-4
eBook Packages: EngineeringEngineering (R0)