NDLI: An interval type-2 fuzzy c-means algorithm based on spatial information for image segmentation

Content Provider	IEEE Xplore Digital Library
Author	Cunyong Qiu Jian Xiao Long Yu Lu Han
Copyright Year	2011
Description	Author affiliation: College of Electrical Engineering, Southwest Jiaotong University, Chengdu, China (Cunyong Qiu; Jian Xiao; Long Yu; Lu Han)
Abstract	Fuzzy c-means algorithm (FCM) is a classic algorithm used in image segmentation. However, FCM is founded with type-1 fuzzy sets, which cannot handle the uncertainties existing in images and algorithm itself. The interval type-2 fuzzy c-means algorithm (IT2FCM) has better performance on handling uncertainties. But for image segmentation, IT2FCM hasn't taken the spatial information of images into account, which makes the segmentation result not ideal enough. In order to incorporate spatial information, an extension of IT2FCM is proposed here. And the result of image segmentation using the proposed algorithm shows that the algorithm has better performance on suppressing noise and better effects on segmenting images compared with FCM-based algorithms and IT2FCM.
Starting Page	545
Ending Page	549
File Size	634138
Page Count	5
File Format	PDF
ISBN	9781612841809
e-ISBN	9781612841816
DOI	10.1109/FSKD.2011.6019569
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Fuzzy sets FCM Uncertainty Noise image segmentation Clustering algorithms Prototypes Partitioning algorithms spatial information type-2 fuzzy
Content Type	Text
Resource Type	Article

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