eprintid: 19026
rev_number: 17
eprint_status: archive
userid: 8119
dir: disk0/00/01/90/26
datestamp: 2016-01-22 01:08:08
lastmod: 2016-02-03 01:50:41
status_changed: 2016-01-22 01:08:08
type: article
metadata_visibility: show
contact_email: shofwatul.uyun@uin-suka.ac.id
creators_name: 'Uyun, Shofwatul
title: Improving Multilevel Thresholding Algorithm Using Ultrafuzziness Optimization Based on Type-II Gaussian Fuzzy Sets
ispublished: pub
subjects: TB
subjects: pen_dosen
subjects: sains
divisions: artkl
full_text_status: public
keywords: Multilevel Thresholding, Ultrafuzziness, Fuzzy Sets, Type II, Gaussian
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 amongother 
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 techniquesby 
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.
date: 2016-01-23
publication: Journal of Theoretical and Applied Information Technology
volume: 83
number: 2
publisher: Little Lion Scientific Islamabad Pakistan
pagerange: 283-290
id_number: http://www.jatit.org/volumes/Vol83No2/16Vol83No2.pdf
refereed: TRUE
issn: 18173195
official_url: http://www.jatit.org/
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citation:   'Uyun, Shofwatul  (2016) Improving Multilevel Thresholding Algorithm Using Ultrafuzziness Optimization Based on Type-II Gaussian Fuzzy Sets.  Journal of Theoretical and Applied Information Technology, 83 (2).  pp. 283-290.  ISSN 18173195     
document_url: https://digilib.uin-suka.ac.id/id/eprint/19026/1/16Vol83No2%20JATIT.pdf