Simulated annealing for texture segmentation with Markov models

Date

1989

Editor(s)

Advisor

Supervisor

Co-Advisor

Co-Supervisor

Instructor

Source Title

Proceedings of the International Workshop on Industrial Applications of Machine Intelligence and Vision, MIV 1989

Print ISSN

Electronic ISSN

Publisher

IEEE

Volume

Issue

Pages

118 - 123

Language

English

Journal Title

Journal ISSN

Volume Title

Series

Abstract

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.

Course

Other identifiers

Book Title

Citation