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

Geometry-based image retrieval in binary image databases.

Naif Alajlan1, Mohamed S Kamel, George H Freeman

  • 1Department of Electrical Engineering, Engineering College, King Saud University, Saudi Arabia. najlan@ksu.edu.sa

IEEE Transactions on Pattern Analysis and Machine Intelligence
|April 19, 2008
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

Phenotypic and genotypic characterization of biofilm-forming Escherichia coli from subclinical bovine mastitis and association with antimicrobial resistance.

BMC veterinary research·2026
Same author

Impacts of variable operating conditions on flux and energy efficiency of air gap membrane distillation for brine management.

Scientific reports·2026
Same author

Concurrent evaluation of oxidative stress biomarkers, cytokine expression, molecular identification, and histopathological findings in sheep naturally infected with Fasciola hepatica.

Veterinary parasitology·2026
Same author

Date seed-and licorice-derived nanoemulsions inhibit clinostomid metacercariae recovered from naturally infected Nile tilapia (Oreochromis niloticus): First report.

Veterinary parasitology·2026
Same author

ZnNPs and senps co-adjuvants deliver superior and long-lasting protection: first report in inactivated Rift Valley fever vaccines for sheep.

Tropical animal health and production·2025
Same author

Hippobosca equina: Influences on oxidative stress and immune-regulating cytokine responses in horses.

Medical and veterinary entomology·2025
Same journal

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective.

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

Learning Topology-Aware Representations via Test-Time Adaptation for Anomaly Segmentation.

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

A new geometry-based image retrieval system uses curvature trees (CT) to model object shape and topology in multi-object images. This method enhances image matching accuracy for medical and shape databases.

Area of Science:

  • Computer Vision
  • Image Processing
  • Pattern Recognition

Background:

  • Content-based image retrieval (CBIR) for multi-object images remains challenging.
  • Existing methods often struggle to represent complex object relationships and shapes effectively.

Purpose of the Study:

  • To develop a geometry-based image retrieval system for multi-object images.
  • To model both shape and topology of image objects using a structured representation.
  • To measure image similarity based on structural and shape attributes.

Main Methods:

  • A novel structured representation, the curvature tree (CT), is proposed to model object shape and topology.
  • The hierarchy of the CT captures inclusion relationships between objects.
  • Triangle-area representation (TAR) is used for shape-based matching within the CT.

Related Experiment Videos

  • Maximum similarity subtree isomorphism (MSSI) algorithm, employing dynamic programming, measures image similarity.

    • Main Results:

    • The proposed matching scheme aligns with human perception of multi-object images.
    • Experiments on large datasets (13,500 medical images, 1,400 MPEG-7 shapes) demonstrate high effectiveness.
    • The system accurately retrieves relevant images based on geometry and topology.

    Conclusions:

    • The developed curvature tree (CT) and MSSI approach provide an effective solution for geometry-based image retrieval.
    • The method successfully models complex object relationships and shapes in multi-object images.
    • This technique shows significant potential for applications in medical imaging and general shape retrieval.