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A Multiresolution Threshold Selection Method Based on Training

  • J. R. Martinez-de Dios
  • A. Ollero
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3211)

Abstract

This paper presents a new training-based threshold selection method for grey level images. One of the main limitations of existing threshold selection methods is the lack of capacity of adaptation to specific vision applications. The proposed method represents a procedure to adapt threshold selection methods to specific applications. The proposed method is based on the analysis of multiresolution decompositions of the image histogram, which is supervised by fuzzy systems in which the particularities of the specific applications were introduced. The method has been extensively applied in various computer vision applications, one of which is described in this paper.

Keywords

Training Image Fuzzy Inference System Threshold Selection Thresholded Image Mode Interpretation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • J. R. Martinez-de Dios
    • 1
  • A. Ollero
    • 1
  1. 1.Grupo de Robótica, Visión y Control, Departamento de Ingeniería de Sistemas y AutomáticaEscuela Superior de Ingenieros. Universidad de SevillaSevillaSpain

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