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Journal of Electronic Imaging

Unsupervised texture segmentation using a nonlinear energy optimization method
Author(s): Sasan Mahmoodi; Bayan S. Sharif
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Paper Abstract

A nonlinear functional is considered for segmentation of images containing structural textures. A structural texture pattern in an image is characterized by a certain amplitude spectrum, and segmentation of different patterns is obtained by detecting different regions with different amplitude spectra. A gradient-descent-based algorithm is proposed by deriving equations minimizing the functional. This algorithm, implementing the solutions minimizing the functional, is based on the level set method. An effective method employed in this algorithm is shown to be robust in a noisy environment. Experimental results demonstrate that the proposed method outperforms segmentation obtained by using the simulated annealing algorithm based on Gaussian Markov random fields.

Paper Details

Date Published: 1 July 2006
PDF: 8 pages
J. Electron. Imaging. 15(3) 033006 doi: 10.1117/1.2234370
Published in: Journal of Electronic Imaging Volume 15, Issue 3
Show Author Affiliations
Sasan Mahmoodi, Univ. of Newcastle Upon Tyne (United Kingdom)
Bayan S. Sharif, Univ. of Newcastle Upon Tyne (United Kingdom)


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