1 July 2006 Unsupervised texture segmentation using a nonlinear energy optimization method
Author Affiliations +
J. of Electronic Imaging, 15(3), 033006 (2006). doi:10.1117/1.2234370
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.
Sasan Mahmoodi, Bayan S. Sharif, "Unsupervised texture segmentation using a nonlinear energy optimization method," Journal of Electronic Imaging 15(3), 033006 (1 July 2006). http://dx.doi.org/10.1117/1.2234370

Image segmentation

Image processing algorithms and systems


Expectation maximization algorithms

Detection and tracking algorithms

Image filtering

Reconstruction algorithms

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