Robust FCM Algorithm with Local and Gray Information for Image Segmentation

Joint Authors

Barrah, Hanane
Cherkaoui, Abdeljabbar
Sarsri, Driss

Source

Advances in Fuzzy Systems

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

Mathematics

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