IMPROVING MULTILEVEL THRESHOLDING ALGORITHM USING ULTRAFUZZINESS OPTIMIZATION BASED ON TYPE-II GAUSSIAN FUZZY SETS

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

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Abstract

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

Item Type: Article
Uncontrolled Keywords: Multilevel Thresholding, Ultrafuzziness, Fuzzy Sets, Type II, Gaussian
Subjects: Sains
Divisions: Artikel (Terbitan Luar UIN)
Depositing User: Sugeng Hariyanto, SIP (sugeng.hariyanto@uin-suka.ac.id)
Date Deposited: 11 Feb 2016 15:47
Last Modified: 23 Feb 2016 14:03
URI: http://digilib.uin-suka.ac.id/id/eprint/19282

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