Image thresholding using type II fuzzy sets

  • Authors:

  • Hamid R. Tizhoosh

  • Affiliations:

  • Pattern Analysis and Machine Intelligence Laboratory, Systems Design Engineering, University of Waterloo, 200 University Avenue West, ON, Canada N2L 3G1

  • Venue:
  • Pattern Recognition
  • Year:
  • 2005

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Abstract

Image thresholding is a necessary task in some image processing applications. However, due to disturbing factors, e.g. non-uniform illumination, or inherent image vagueness, the result of image thresholding is not always satisfactory. In recent years, various researchers have introduced new thresholding techniques based on fuzzy set theory to overcome this problem. Regarding images as fuzzy sets (or subsets), different fuzzy thresholding techniques have been developed to remove the grayness ambiguity/vagueness during the task of threshold selection. In this paper, a new thresholding technique is introduced which processes thresholds as type II fuzzy sets. A new measure of ultrafuzziness is also introduced and experimental results using laser cladding images are provided.