Ultrafuzziness Optimization Based on Type II Fuzzy Sets for Image Thresholding
نویسندگان
چکیده
Image thresholding is one of the processing techniques to provide high quality preprocessed image. Image vagueness and bad illumination are common obstacles yielding in a poor image thresholding output. By assuming image as fuzzy sets, several different fuzzy thresholding techniques have been proposed to remove these obstacles during threshold selection. In this paper, we proposed an algorithm for thresholding image using ultrafuzziness optimization to decrease uncertainty in fuzzy system by common fuzzy sets like type II fuzzy sets. Optimization was conducted by involving ultrafuzziness measurement for background and object fuzzy sets separately. Experimental results demonstrated that the proposed image thresholding method had good performances for images with high vagueness, low level contrast, and grayscale ambiguity.
منابع مشابه
Image thresholding using type II fuzzy sets
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 set...
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متن کاملComment on: "Image thresholding using type II fuzzy sets"
This short comment aims at providing connections between the algorithm for image thresholding using type II fuzzy sets, recently proposed by Tizhoosh in Ref. [1], and Atanassov’s intuitionistic fuzzy sets (A-IFSs), as well as pointing out some terminological issues. The idea of applying higher-order fuzzy sets for image thresholding discussed in Ref. [1] is interesting and promising; however, s...
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