Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A bond percolation-based model for image segmentation.

I Hussain1, T R Reed

  • 1Gen. DataComm. Inc., Middlebury, CT.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1997
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Prompt-directed ambient artificial intelligence for automated multidisciplinary tumor board documentation.

Annals of oncology : official journal of the European Society for Medical Oncology·2026
Same author

Development and evaluation of a lateral flow-based portable optical system for determination of the pregnancy status of dairy cows.

Journal of dairy science·2024
Same author

Estimation of genetic components, heterosis and combining ability of elite Pakistani wheat varieties for yield attributing traits and stripe rust response.

Vavilovskii zhurnal genetiki i selektsii·2023
Same author

Evidence of novel Treponema phylotypes implicated in contagious ovine digital dermatitis and association of treponemes with major lameness causing foot pathogens.

Microbial pathogenesis·2023
Same author

Can honey improve the quality of cryopreserved cross bred ram semen added to tris egg yolk extender?

Cryo letters·2023
Same author

Extra-modification of zirconium dioxide for potential photocatalytic applications towards environmental remediation: A critical review.

Journal of environmental management·2022
Same journal

Hyperbolic Cycle Alignment for Infrared-Visible Image Fusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Learning Gaze Synthesizer via 3D-eye Controlled Diffusion and Cross-domain Feature Alignment.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Underlying Semantic Diffusion for Effective and Efficient In-Context Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

DiffRES: Unleashing Text-to-Image Diffusion Models for Generative Referring Expression Segmentation without Information Leakage.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Location Matters: Frequency-Spatial Dual Space Adaptation for Cross-Domain Few-Shot Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

BayeTopo: Bayesian-based Topology-guided Learning for Vascular Imaging Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

This study introduces a new bond percolation method to define Gibbs-Markov model parameters for image analysis. This approach enables multiresolution image segmentation by creating multiscale descriptions of these parameters.

Area of Science:

  • Computer Vision
  • Statistical Physics
  • Image Processing

Background:

  • Gibbs-Markov models are widely used for image segmentation.
  • Determining clique potential parameters is crucial for model accuracy.
  • Existing methods may lack multiscale capabilities.

Purpose of the Study:

  • To develop a novel bond percolation-based approach for determining Gibbs-Markov model clique potential parameters.
  • To establish a multiscale description of these parameters using renormalization group transformations.
  • To apply the derived parameters for multiresolution image segmentation.

Main Methods:

  • Utilizing bond percolation theory to define clique potential parameters.
  • Applying renormalization group transformations for multiscale analysis.

Related Experiment Videos

  • Implementing the multiscale parameters for image segmentation.

    • Main Results:

    • Successfully determined clique potential parameters as a function of local image characteristics.
    • Generated a multiscale description of the clique potential parameters.
    • Achieved multiresolution image segmentation using the novel approach.

    Conclusions:

    • The bond percolation-based method provides an effective way to parameterize Gibbs-Markov models.
    • The renormalization group transformation enables multiscale analysis for improved segmentation.
    • This work offers a novel framework for multiresolution image segmentation.