Image segmentation of noisy digital images using extended fuzzy C-means clustering algorithm Online publication date: Wed, 05-Jun-2013
by Prabhjot Kaur; A.K. Soni; Anjana Gosain
International Journal of Computer Applications in Technology (IJCAT), Vol. 47, No. 2/3, 2013
Abstract: Fuzzy C-Means algorithm fails to segment the noisy image properly. In this paper, we present an algorithm called Extended Fuzzy C means (EFCM), which pre-processes the image to reduce the noise effect and then apply FCM algorithm for image segmentation. Pre-processing of image is influenced by the direct eight neighbourhood pixels of every pixel of an image under consideration. Proposed algorithm has least execution time and it yields regions more homogeneous than those of other techniques. It removes noisy spots and is less sensitive to noise. The proposed technique is a powerful method for noisy image segmentation compared to other image segmentation techniques.
Online publication date: Wed, 05-Jun-2013
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org