Robust FCM Algorithm with Local and Gray Information for Image Segmentation
Joint Authors
Barrah, Hanane
Cherkaoui, Abdeljabbar
Sarsri, Driss
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-10-20
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The FCM (fuzzy c-mean) algorithm has been extended and modified in many ways in order to solve the image segmentation problem.
However, almost all the extensions require the adjustment of at least one parameter that depends on the image itself.
To overcome this problem and provide a robust fuzzy clustering algorithm that is fully free of the empirical parameters and noise type-independent, we propose a new factor that includes the local spatial and the gray level information.
Actually, this work provides three extensions of the FCM algorithm that proved their efficiency on synthetic and real images.
American Psychological Association (APA)
Barrah, Hanane& Cherkaoui, Abdeljabbar& Sarsri, Driss. 2016. Robust FCM Algorithm with Local and Gray Information for Image Segmentation. Advances in Fuzzy Systems،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1095057
Modern Language Association (MLA)
Barrah, Hanane…[et al.]. Robust FCM Algorithm with Local and Gray Information for Image Segmentation. Advances in Fuzzy Systems No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1095057
American Medical Association (AMA)
Barrah, Hanane& Cherkaoui, Abdeljabbar& Sarsri, Driss. Robust FCM Algorithm with Local and Gray Information for Image Segmentation. Advances in Fuzzy Systems. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1095057
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1095057