ePrints

Contour evolution scheme for variational image segmentation and smoothing

Lookup NU author(s): Dr Sasan Mahmoodi, Professor Bayan Sharif

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.

Abstract

An algorithm, based on the Mumford-Shah (M-S) functional, for image contour segmentation and object smoothing in the presence of noise is proposed. However, in the proposed algorithm, contour length minimisation is not required and it is demonstrated that the M-S functional without contour length minimisation becomes an edge detector. Optimisation of this nonlinear functional is based on the method of calculus of variations, which is implemented by using the level set method. Fourier and Legendre's series are also employed to improve the segmentation performance of the proposed algorithm. The segmentation results clearly demonstrate the effectiveness of the proposed approach for images with low signal-to-noise ratios. © The Institution of Engineering and Technology 2007.

Publication metadata

Author(s): Mahmoodi S, Sharif BS

Publication type: Article

Publication status: Published

Journal: IET Image Processing

Year: 2007

Volume: 1

Issue: 3

Pages: 287-294

ISSN (print): 1751-9659

ISSN (electronic): 1751-9667

Publisher: The Institution of Engineering and Technology

URL: http://dx.doi.org/10.1049/iet-ipr:20050188

DOI: 10.1049/iet-ipr:20050188

Altmetrics

Share