By Topic

Simulated annealing for texture segmentation with Markov models

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yalabik, M.C. ; Dept. of Phys., Bilkent Univ., Ankara, Turkey ; Yalabik, N.

Binary textured images are segmented into regions of different textures. The binary Markov model is used, and model parameters are assumed to be unknown prior to segmentation. The parameters are estimated using a weighted-least-squares method, while segmentation is performed iteratively using simulated annealing. To speed up the annealing process, an initial coarse segmentation algorithm that quickly determines the approximate region categories using k-means clustering algorithm is used. The results look promising, and the computational costs can be reduced further by optimization of the computations

Published in:

Industrial Applications of Machine Intelligence and Vision, 1989., International Workshop on

Date of Conference:

10-12 Apr 1989