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

Edge detection revisited.

Felice Andrea Pellegrino1, Walter Vanzella, Vincent Torre

  • 1Department of Mathematics and Computer Science (DIMI), University of Udine, Udine 33100, Italy.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|October 16, 2004
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

Application of Computer Vision to the Automated Extraction of Metadata from Natural History Specimen Labels: A Case Study on Herbarium Specimens.

Plants (Basel, Switzerland)·2026
Same author

Exosomal TNF-α mediates voltage-gated Na+ channel 1.6 overexpression and contributes to brain tumor-induced neuronal hyperexcitability.

The Journal of clinical investigation·2024
Same author

Mechanisms of Glioblastoma Replication: Ca2+ Flares and Cl- Currents.

Molecular cancer research : MCR·2024
Same author

Structural heterogeneity of the ion and lipid channel TMEM16F.

Nature communications·2024
Same author

Unfolding and identification of membrane proteins in situ.

eLife·2022
Same author

The dual action of glioma-derived exosomes on neuronal activity: synchronization and disruption of synchrony.

Cell death & disease·2022

This study introduces a novel edge detection algorithm that simultaneously detects edges at multiple scales, thin bars, and junctions. It outperforms the Canny edge detector in image reconstruction and structure-from-motion tasks.

Area of Science:

  • Computer Vision
  • Image Processing
  • Computational Imaging

Background:

  • Traditional edge detection methods struggle with simultaneous multi-scale edge detection, thin structures, and junctions.
  • Existing algorithms often require image-specific parameter tuning, limiting their general applicability.

Purpose of the Study:

  • To develop a robust edge detection algorithm addressing limitations in detecting step edges across scales, thin bars, and trihedral junctions.
  • To create an image-independent edge detection method with consistent performance.

Main Methods:

  • Combines extensive spatial filtering with classical computer vision techniques and novel algorithms.
  • Step edges detected via local maxima from summed energy over directional odd filters at various scales.
  • Thin roof edges identified by maxima of summed energy over narrow odd/even filters.

Related Experiment Videos

  • Junctions precisely detected and recovered using directional filter outputs.

    • Main Results:

    • The proposed algorithm successfully detects step edges across scales, thin bars, and trihedral junctions.
    • Demonstrates parameter-free operation by setting a fixed noise-based contrast threshold.
    • Outperforms the Canny edge detector in quantitative comparisons for image recovery and structure-from-motion tasks.

    Conclusions:

    • The novel edge detection scheme offers significant improvements over existing methods, including the Canny detector.
    • Achieves superior performance in complex image analysis tasks due to its comprehensive approach to edge feature extraction.