Image thresholding using restricted equivalence functions and maximizing the measures of similarity

  • Authors:

  • H. Bustince;E. Barrenechea;M. Pagola

  • Affiliations:

  • Departamento de Automática y Computación, Universidad Pública de Navarra, Campus Arrosadia s/n, P.O. Box 31006, Pamplona, Spain;Departamento de Automática y Computación, Universidad Pública de Navarra, Campus Arrosadia s/n, P.O. Box 31006, Pamplona, Spain;Departamento de Automática y Computación, Universidad Pública de Navarra, Campus Arrosadia s/n, P.O. Box 31006, Pamplona, Spain

  • Venue:
  • Fuzzy Sets and Systems
  • Year:
  • 2007

Quantified Score

Hi-index 0.21

Visualization

Abstract

In this paper we apply restricted equivalence functions to the computation of the threshold of an image. In the first part we present an algorithm for obtaining the best threshold of a grayscale image with a single object. In the second part we study different algorithms for calculating the optimal threshold. Then we analyze two algorithms for obtaining a sequence of optimal thresholds in images with several objects. Lastly, we compare our results with those obtained with other methods and carry out a study of the time efficiency of the methods we propose.