• DocumentCode
    1617051
  • Title

    Quasi-global oppositional fuzzy thresholding

  • Author

    Tizhoosh, Hamid R. ; Sahba, Farhang

  • Author_Institution
    Pattern Anal. & Machine Intell. Lab., Univ. of Waterloo, Waterloo, ON, Canada
  • fYear
    2009
  • Firstpage
    1346
  • Lastpage
    1351
  • Abstract
    Opposition-based computing is the paradigm for incorporating entities along with their opposites within the search, optimization and learning mechanisms. In this work, we introduce the notion of "opposite fuzzy sets" in order to use the entropy difference between a fuzzy set and its opposite to carry out object discrimination in digital images. A quasi-global scheme is used to execute the calculations, which can be employed by any other existing thresholding technique. Results for prostate ultrasound images have been provided to verify the performance whereas expert\´s markings have been used as gold standard.
  • Keywords
    fuzzy set theory; image segmentation; learning (artificial intelligence); optimisation; search problems; digital image; entropy; image segmentation; learning mechanism; object discrimination; opposite fuzzy set; opposition-based computing; optimization; quasi-global oppositional fuzzy thresholding; search problem; Design engineering; Fuzzy sets; Fuzzy systems; Image segmentation; Laboratories; Machine intelligence; Neural networks; Pattern analysis; System analysis and design; Ultrasonic imaging; Fuzzy sets; antony; antonym; complement; image thresholding; opposite fuzzy sets; opposition; segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
  • Conference_Location
    Jeju Island
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-3596-8
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2009.5276887
  • Filename
    5276887