Automatic segmentation of multi-class images with NLS model
by K. Punnam Chandar; T. Satya Savithri; B. Swarnalatha
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 28, No. 1, 2018

Abstract: In this paper, automatic segmentation of multi-class images problem is considered. The 1D histogram of the multi-class image is approximated using Gaussian functions and the unknown parameters of the Gaussian functions are estimated using Non-linear Least Squares (NLS) optimisation; thereby the problem of segmentation of unknown image class is modelled as an optimisation problem. Further, the parameter estimation accuracy is improved by using the Pearson linear correlation coefficient as a regularisation term of the objective function. The experimental results demonstrate the NLS algorithm ability to estimate the parameters of the Gaussian functions and thereby automatically determine the multi-thresholds for segmentation.

Online publication date: Mon, 03-Sep-2018

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 Biomedical Engineering and Technology (IJBET):
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