Chapter

Pattern Recognition and Image Analysis

Volume 3523 of the series Lecture Notes in Computer Science pp 83-90

Improving the Discrimination Capability with an Adaptive Synthetic Discriminant Function Filter

  • J. Ángel González-FragaAffiliated withDepartment of Computer Sciences, Division of Applied Physics, CICESE
  • , Víctor H. Díaz-RamírezAffiliated withDepartment of Computer Sciences, Division of Applied Physics, CICESE
  • , Vitaly KoberAffiliated withDepartment of Computer Sciences, Division of Applied Physics, CICESE
  • , Josué Álvarez-BorregoAffiliated withOptics Department, Division of Applied Physics, CICESE

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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.