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
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;
Conference_Titel :
Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
Conference_Location :
Jeju Island
Print_ISBN :
978-1-4244-3596-8
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2009.5276887