Improving the Discrimination Capability with an Adaptive Synthetic Discriminant Function Filter

  • J. Ángel González-Fraga
  • Víctor H. Díaz-Ramírez
  • Vitaly Kober
  • Josué Álvarez-Borrego
Conference paper

DOI: 10.1007/11492542_11

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3523)
Cite this paper as:
González-Fraga J.Á., Díaz-Ramírez V.H., Kober V., Álvarez-Borrego J. (2005) Improving the Discrimination Capability with an Adaptive Synthetic Discriminant Function Filter. In: Marques J.S., Pérez de la Blanca N., Pina P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg

Abstract

In this paper a new adaptive correlation filter based on synthetic discriminant functions (SDF) for reliable pattern recognition is proposed. The information about an object to be recognized and false objects as well as background to be rejected is used in an iterative procedure to design the adaptive correlation filter with a given discrimination capability. Computer simulation results obtained with the proposed filter in test scenes are compared with those of various correlation filters in terms of discrimination capability.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • J. Ángel González-Fraga
    • 1
  • Víctor H. Díaz-Ramírez
    • 1
  • Vitaly Kober
    • 1
  • Josué Álvarez-Borrego
    • 2
  1. 1.Department of Computer Sciences, Division of Applied PhysicsCICESEEnsenadaMexico
  2. 2.Optics Department, Division of Applied PhysicsCICESEEnsenadaMexico

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