Target recognition by Fast Optimal Fuzzy C-Means image segmentation
by Junwei Tian, Qing E. Wu, Yongxuan Huang, Tuo Wang
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 4, No. 2, 2011

Abstract: We propose a novel Fast Optimal Fuzzy C-Means (FOFCM) clustering algorithm to improve target recognition in image processing. FOFCM can find the best clustering number of images by exploiting the characteristics of the given images, and reduce the segmentation time significantly at the same time. Experiments on serials images are employed to demonstrate the performance of FOFCM. The experiment results show that FOFCM has significantly better performance and lower complexity than previously proposed approaches. The correct recognition rate is increased by 29.24%, which is 94.59%. The clustering efficiency is improved by 6-132 times.

Online publication date: Fri, 13-Mar-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
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 Signal and Imaging Systems Engineering (IJSISE):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your 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 subs@inderscience.com