Snake based Unsupervised Texture Segmentation using Gaussian Markov Random Field Models
Snake based Unsupervised Texture Segmentation using Gaussian Markov Random Field Models
A functional for unsupervised texture segmentation is investigated in this paper. An auto-normal model based on Markov Random Fields is employed to model textures. The functional investigated here is optimized with respect to the model parameters and the evolving contour to simultaneously estimate model parameters and find the boundaries between textures. Experimental results applied on the textures of the Brodatz album demonstrate the superior performance and the higher speed of convergence of this algorithm in comparison with a traditional stochastic algorithm in the literature.
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Gunn, Steve
306af9b3-a7fa-4381-baf9-5d6a6ec89868
14 September 2011
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Gunn, Steve
306af9b3-a7fa-4381-baf9-5d6a6ec89868
Mahmoodi, Sasan and Gunn, Steve
(2011)
Snake based Unsupervised Texture Segmentation using Gaussian Markov Random Field Models.
18th IEEE International Conference on Image Processing, Brussels, Belgium.
11 - 14 Sep 2011.
Record type:
Conference or Workshop Item
(Poster)
Abstract
A functional for unsupervised texture segmentation is investigated in this paper. An auto-normal model based on Markov Random Fields is employed to model textures. The functional investigated here is optimized with respect to the model parameters and the evolving contour to simultaneously estimate model parameters and find the boundaries between textures. Experimental results applied on the textures of the Brodatz album demonstrate the superior performance and the higher speed of convergence of this algorithm in comparison with a traditional stochastic algorithm in the literature.
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SnakeGMRF.pdf
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SnakeGMRF.pdf
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Published date: 14 September 2011
Additional Information:
Event Dates: 11-14 September 2011
Venue - Dates:
18th IEEE International Conference on Image Processing, Brussels, Belgium, 2011-09-11 - 2011-09-14
Organisations:
Electronic & Software Systems, Southampton Wireless Group
Identifiers
Local EPrints ID: 272213
URI: http://eprints.soton.ac.uk/id/eprint/272213
PURE UUID: 3e56ed9e-c576-47ac-8af2-f7370f7c434b
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Date deposited: 18 Apr 2011 16:18
Last modified: 14 Mar 2024 09:49
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Contributors
Author:
Sasan Mahmoodi
Author:
Steve Gunn
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