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Contour evolution scheme for variational image segmentation and smoothing

Contour evolution scheme for variational image segmentation and smoothing
Contour evolution scheme for variational image segmentation and smoothing
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.
287-294
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Sharif, Bayan
d57a4cae-a6f0-4ab3-b2d8-ef594a75857f
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Sharif, Bayan
d57a4cae-a6f0-4ab3-b2d8-ef594a75857f

Mahmoodi, Sasan and Sharif, Bayan (2007) Contour evolution scheme for variational image segmentation and smoothing. IET Image Processing, 1 (3), 287-294.

Record type: Article

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.

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Published date: June 2007
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 265877
URI: http://eprints.soton.ac.uk/id/eprint/265877
PURE UUID: a36d2bb5-c819-486f-8cf1-acc024be2fec

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Date deposited: 10 Jun 2008 09:54
Last modified: 19 Jul 2019 22:22

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Contributors

Author: Sasan Mahmoodi
Author: Bayan Sharif

University divisions

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