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

Optimal approach for fast object-template matching.

András Hajdu1, Ioannis Pitas

  • 1Department of Informatics, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece. hajdua@aiia.csd.auth.gr

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|August 11, 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

Novel common target genes for breast cancer and colorectal cancer: a Mendelian randomization and spatial transcriptomics study.

Discover oncology·2025
Same author

LIX: Implicitly Infusing Spatial Geometric Prior Knowledge Into Visual Semantic Segmentation for Autonomous Driving.

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

The microbiome in cancer.

iMeta·2025
Same author

Space Dentistry Combined With Remote and AI Technologies, a Necessity for Long-Term Stays: Thoughts of US Astronauts' Unexpected Stay.

Oral diseases·2025
Same author

Improving Cell Detection and Tracking in Microscopy Images Using YOLO and an Enhanced DeepSORT Algorithm.

Sensors (Basel, Switzerland)·2025
Same author

A Hybrid Compact Convolutional Transformer with Bilateral Filtering for Coffee Berry Disease Classification.

Sensors (Basel, Switzerland)·2025
Same journal

Style-Aware Contrastive Test-Time Adaptation: A Dual-Cache Model for Robust Vision-Language Alignment.

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

Semantic Frame Interpolation.

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

Physics-Guided Cross-Modal Decoupling with Test-Time Adaptation for Hyperspectral Image Restoration.

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

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

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

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

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

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

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

This study introduces a new algorithm to simplify object descriptions for faster matching. By reducing pixel data using centroidal Voronoi tessellations, computation is decreased while maintaining accuracy in object recognition tasks.

Area of Science:

  • Computer Vision
  • Image Processing
  • Pattern Recognition

Background:

  • Object matching often requires significant computational resources.
  • Simplifying object descriptions can improve efficiency.
  • Existing methods may not optimally reduce descriptive complexity.

Purpose of the Study:

  • To propose a novel algorithm for optimal object description reduction.
  • To decrease computational needs in object matching.
  • To enhance the efficiency of matching processes.

Main Methods:

  • Development of a theoretical framework based on centroidal Voronoi tessellations.
  • Integration of the algorithm within the chamfer matching framework.
  • Application to 2-D contour and region-like object matching.

Related Experiment Videos

Main Results:

  • Demonstrated reduction in computation by simplifying object representations.
  • Validated the approach for 2-D contour and region-like object matching.
  • Showcased effective use of simplified object parts for human recognition.

Conclusions:

  • The proposed algorithm offers an effective method for optimal object description reduction.
  • Centroidal Voronoi tessellations provide a robust theoretical basis for simplification.
  • The simplification approach leads to valid and efficient template replacements in object matching.