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

Mask-based second-generation connectivity and attribute filters.

Georgios K Ouzounis1, Michael H F Wilkinson

  • 1Institute for Mathematics and Computing Science, University of Groningen, 9700 AV Groningen, The Netherlands.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|April 14, 2007
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

A Shared-Memory Parallel Alpha-Tree Algorithm for Extreme Dynamic Ranges.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2025
Same author

Evaluation of Alpha-Trees for Hierarchical Segmentation by Horizontal Cuts.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2025
Same author

Stripe noise removal in conductive atomic force microscopy.

Scientific reports·2024
Same author

A Fast Alpha-Tree Algorithm for Extreme Dynamic Range Pixel Dissimilarities.

IEEE transactions on pattern analysis and machine intelligence·2023
Same author

Distributed Connected Component Filtering and Analysis in 2D and 3D Tera-Scale Data Sets.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2021
Same author

A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images.

IEEE transactions on pattern analysis and machine intelligence·2017
Same journal

TraGraph-GS: Trajectory Graph-based Gaussian Splatting for Arbitrary Large-Scale Scene Rendering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

SWIFT: A Small-World Interaction Framework for Flow-Aware Trajectory Prediction in Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

HardFlow: Hard-Constrained Sampling for Flow-Matching Models Via Trajectory Optimization.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Industrial Brain: Self-Evolving Neuro-Symbolic Autonomy with Causal Resilience for Cyber-Physical Systems.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Adaptive Hardness-Driven Dictionary Distillation for Incomplete Streaming View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026
Same journal

Mixture of Global and Local Experts with Diffusion Transformer for Controllable Face Generation.

IEEE transactions on pattern analysis and machine intelligence·2026
See all related articles

This study introduces mask-based connectivity, a novel approach to image analysis that overcomes limitations of standard connected filters. The efficient Max-Tree algorithm enables advanced attribute filtering for better object grouping and partitioning in images.

Area of Science:

  • Image Processing
  • Computer Vision
  • Mathematical Morphology

Background:

  • Connected filters are edge-preserving operators crucial for image analysis.
  • Standard 4 and 8-connectivity are often too rigid for complex groupings like object clusters.
  • Existing frameworks for generalized connectivity can be dependent on preselected operators.

Purpose of the Study:

  • To extend the theory of second-generation connectivity for more flexible image analysis.
  • To develop an efficient algorithm for computing attribute filters based on generalized connectivities.
  • To address the limitations of existing frameworks in modeling generalized groupings.

Main Methods:

  • Introduced a new concept: mask-based connectivity, a type of second-generation connectivity.

Related Experiment Videos

  • Developed an efficient algorithm using the Max-Tree data structure.
  • Adapted a Dual-Input Max-Tree algorithm for attribute filters with second-generation connectivity.

    • Main Results:

    • The proposed mask-based connectivity eliminates dependencies on preselected operators and expands connectivity options.
    • The new Max-Tree algorithm efficiently computes attribute filters for images with second-generation connectivity.
    • Computational performance (CPU-time) of the new algorithm is comparable to existing methods, with deviations typically under 10%.

    Conclusions:

    • Mask-based connectivity offers a more versatile framework for image analysis than traditional methods.
    • The efficient Max-Tree algorithm facilitates the application of advanced attribute filters for complex image segmentation tasks.
    • This work advances morphological image processing by enabling more sophisticated modeling of image structures.