Thresholding of pathological images using Atanassov's intuitionistic fuzzy set Online publication date: Sat, 04-Apr-2015
by Tamalika Chaira
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 7, No. 2, 2015
Abstract: This paper addresses pathological image thresholding schemes using Atanassov's intuitionistic fuzzy set. Three different types of membership functions - Cauchy membership function, Gamma membership function, membership function using restricted equivalence function are used to find out the membership degrees of the pixels of an image. Intuitionistic fuzzy set theory takes into account two uncertainties - the membership degree and non-membership degree. Non-membership degree is not the complement of the membership degree as in fuzzy set theory rather less than or equal to it. Non-membership degree is calculated using Sugeno type intuitionistic fuzzy generator. The use of two uncertainties in the Atanassov's intuitionistic fuzzy set helps in thresholding the images more appropriately. The effectiveness of the algorithm is demonstrated by performing experiment on different types of poorly illuminated pathological blood vessel images using the three types of membership function.
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