Jove
Visualize
Contact Us

Related Experiment Videos

Unsupervised contour closure algorithm for range image edge-based segmentation.

Angel Domingo Sappa1

  • 1Computer Vision Center, 08193 Bellaterra, Barcelona, Spain. angel.sappa@cvc.uab.es

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 17, 2006
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 probabilistic approach for color correction in image mosaicking applications.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2014
Same author

The richer representation the better registration.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2013
Same author

Implicit polynomial representation through a fast fitting error estimation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2011
Same author

Efficient generation of discontinuity-preserving adaptive triangulations from range images.

IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society·2004
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
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

This study introduces an efficient method for extracting closed contours from range image edge points using graph partitioning and minimum spanning trees. The technique effectively closes open contours and removes noise for improved 3D data analysis.

Area of Science:

  • Computer Vision
  • 3D Data Processing
  • Computational Geometry

Background:

  • Extracting closed contours from range images is crucial for 3D object recognition and scene understanding.
  • Existing methods for contour extraction from edge points can be sensitive to noise and may struggle with contour closure.

Purpose of the Study:

  • To present an efficient and robust technique for extracting closed contours from edge points in range images.
  • To reduce the contour closure problem to a minimum spanning tree partitioning problem combined with cost function minimization.

Main Methods:

  • Generate a partially connected graph from input edge points.
  • Compute the minimum spanning tree (MST) of the generated graph.
  • Apply a postprocessing step to remove noisy links and close open contours, forming a single path.

Related Experiment Videos

Main Results:

  • The proposed method successfully extracts closed contours from range image edge points.
  • Experimental results demonstrate the efficiency and effectiveness of the technique on synthetic and real range data.
  • Comparisons with a previous technique show improved performance in contour extraction.

Conclusions:

  • The novel approach effectively addresses the contour closure problem by leveraging graph theory and MST algorithms.
  • This technique offers an efficient solution for deriving meaningful boundary representations from noisy edge data in range images.
  • The method has potential applications in various fields requiring precise 3D shape analysis.