{"title":"Intuitionistic type-2 fuzzy set approach to image thresholding","authors":"Tarn Van Nghiem, D. Nguyen, L. Ngo","doi":"10.1109/SOCPAR.2013.7054128","DOIUrl":null,"url":null,"abstract":"In this paper, an image thresholding method based on Intuitionistic Type-2 Fuzzy Sets (InT2FS) method is introduced for the segmentation problems. Besides, intuitionistic type-2 fuzzy set has been formed as an extension of intuitionistic fuzzy set for handling uncertainty. As we know, the image data which usually contains noises or uncertainty so then utilizing the advantages of the InT2FS, we have introduced a thresholding algorithm using InT2FS for image thresholding. Experimental results with different types of images show that the proposed algorithm is better than the traditional thresholding algorithms especially with noisy images.","PeriodicalId":315126,"journal":{"name":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","volume":"65 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Soft Computing and Pattern Recognition (SoCPaR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOCPAR.2013.7054128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper, an image thresholding method based on Intuitionistic Type-2 Fuzzy Sets (InT2FS) method is introduced for the segmentation problems. Besides, intuitionistic type-2 fuzzy set has been formed as an extension of intuitionistic fuzzy set for handling uncertainty. As we know, the image data which usually contains noises or uncertainty so then utilizing the advantages of the InT2FS, we have introduced a thresholding algorithm using InT2FS for image thresholding. Experimental results with different types of images show that the proposed algorithm is better than the traditional thresholding algorithms especially with noisy images.