relation: https://digilib.uin-suka.ac.id/id/eprint/19282/
title: IMPROVING MULTILEVEL THRESHOLDING ALGORITHM USING ULTRAFUZZINESS OPTIMIZATION BASED ON TYPE-II GAUSSIAN FUZZY SETS
creator: UYUN, SHOFWATUL
subject: Sains
description: Image thresholding is one of image processing techniques to help analyze the next phase. Consequently,  choosing a precise method in this step is quite-essential. Image blurs and bad illumination are common  constraints that often influence the effectiveness of the thresholding method. Fuzzy sets is one among other  perceptions in scoring an image. Thus, various thresholding fuzzy techniques have been developed to  eliminate those constraints. This paper proposes the improvement of multilevel thresholding techniques by  using type II fuzzy sets with the function of gaussian membership to access some objects at mammogram to  get fibroglandular tissue areas. The result shows that the proposed technique has a very good achievement  with the average score with misclassification error parameter of 97.86%. This proves that the proposed  algorithm are able to function well to the image with low contrast level and high unclearness level.  Keywords: Multilevel Thresholding, Ultrafuzziness, Fuzzy Sets, Type II, Gaussian
publisher: JATIT
date: 2016-01-20
type: Article
type: PeerReviewed
format: text
language: en
identifier: https://digilib.uin-suka.ac.id/id/eprint/19282/1/SHOFWATUL%20%E2%80%98UYUN%20-%20IMPROVING%20MULTILEVEL%20THRESHOLDING%20ALGORITHM%20USING%20ULTRAFUZZINESS%20OPTIMIZATION%20BASED%20ON%20TYPE-II%20GAUSSIAN%20FUZZY%20SETS.pdf
identifier:   UYUN, SHOFWATUL  (2016) IMPROVING MULTILEVEL THRESHOLDING ALGORITHM USING ULTRAFUZZINESS OPTIMIZATION BASED ON TYPE-II GAUSSIAN FUZZY SETS.  Journal of Theoretical and Applied Information Technology, Vol.83 (No.2).  pp. 283-290.  ISSN 1992-8645     
relation: 1992-8645