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Image Threshold Using A-IFSs Based on Bounded Histograms

  • Pedro Couto
  • Humberto Bustince
  • Vitor Filipe
  • Edurne Barrenechea
  • Miguel Pagola
  • Pedro Melo-Pinto
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4529)

Abstract

Atanassov’s intuitionistic fuzzy sets (A-IFSs) have been used recently to determine the optimal threshold value for gray-level image segmentation [1]. Atanassov’s intuitionistic fuzzy index values are used for representing the unknowledge/ignorance of an expert on determining whether a pixel of the image belongs to the background or the object of the image. This optimal global threshold of the image is computed automatically, regardless of the actual image analysis process.

Although global optimal thresholding techniques give good results under experimental conditions, when dealing with real images having several objects and the segmentation purpose is to point out some application-specific information, one should use heuristic techniques in order to obtain better thresholding results.

This paper introduces an evolution of the above mentioned technique intended for use with such images. The proposed approach takes into account the image and segmentation specificities by using a two-step procedure, with a restricted set of the image gray-levels.

Preliminary experimental results and comparison with other methods are presented.

Keywords

Fuzzy Sets Theory Applications Atanassov’s Intuitionistic Fuzzy Sets (A-IFSs) computer Vision Pattern Recognition Digital Image Processing 

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Pedro Couto
    • 1
  • Humberto Bustince
    • 2
  • Vitor Filipe
    • 1
  • Edurne Barrenechea
    • 2
  • Miguel Pagola
    • 2
  • Pedro Melo-Pinto
    • 1
  1. 1.CETAV – University of Trás-os-Montes e Alto Douro, Ap. 1014, 5001-911 Vila RealPortugal
  2. 2.Departamento de Automática y Computación - Universidad Pública de Navarra, Campus de Arrosadía, s/n, 31006 PamplonaSpain

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