DocumentCode
1545197
Title
A bond percolation-based model for image segmentation
Author
Hussain, Iftekhar ; Reed, Todd R.
Author_Institution
Gen. DataComm. Inc., Middlebury, CT, USA
Volume
6
Issue
12
fYear
1997
fDate
12/1/1997 12:00:00 AM
Firstpage
1698
Lastpage
1704
Abstract
This work presents a novel bond percolation-based approach to determine the clique potential parameters of a Gibbs-Markov model as a function of local characteristics of the underlying image. Using the renormalization group transformation, a multiscale description of the clique potential parameters is formed and used to obtain multiresolution image segmentation
Keywords
Markov processes; image resolution; image segmentation; parameter estimation; percolation; random processes; renormalisation; transforms; Gibbs-Markov model; bond percolation-based model; clique potential parameters; image segmentation; multiscale description; renormalization group transformation; underlying image; Assembly; Automobiles; Bonding; Cancer detection; Crops; Image resolution; Image segmentation; Machine vision; Nearest neighbor searches; Two dimensional displays;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/83.650123
Filename
650123
Link To Document