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

Efficient 2-D grayscale morphological transformations with arbitrary flat structuring elements.

Erik R Urbach1, Michael H F Wilkinson

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

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 31, 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

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

Hyperbolic Cycle Alignment for Infrared-Visible Image Fusion.

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

Learning Gaze Synthesizer via 3D-eye Controlled Diffusion and Cross-domain Feature Alignment.

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

Underlying Semantic Diffusion for Effective and Efficient In-Context Learning.

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

DiffRES: Unleashing Text-to-Image Diffusion Models for Generative Referring Expression Segmentation without Information Leakage.

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

Location Matters: Frequency-Spatial Dual Space Adaptation for Cross-Domain Few-Shot Segmentation.

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

BayeTopo: Bayesian-based Topology-guided Learning for Vascular Imaging Segmentation.

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

This study introduces an efficient algorithm for grayscale morphological operations using flat structuring elements (S.E.). The new method significantly outperforms existing techniques and enables combined filtering with multiple S.E.s in a single operation.

Area of Science:

  • Computer Vision
  • Image Processing
  • Digital Image Analysis

Background:

  • Grayscale morphological operations are fundamental in image processing.
  • Existing algorithms for arbitrary 2-D flat structuring elements (S.E.) have limitations in efficiency and flexibility.
  • Current methods for multiple S.E. filtering require separate computations for each element.

Purpose of the Study:

  • To develop an efficient algorithm for grayscale morphological operations with arbitrary 2-D flat structuring elements (S.E.).
  • To improve computational performance compared to existing methods.
  • To enable efficient filtering with multiple S.E.s in a single operation.

Main Methods:

  • An efficient algorithm for computing grayscale morphological operations.

Related Experiment Videos

  • Utilizes arbitrary 2-D flat structuring elements (S.E.).
  • Algorithm's performance is independent of image content and gray levels.

    • Main Results:

    • The algorithm's computing time is independent of image content and gray levels.
    • Outperforms the Van Droogenbroeck and Talbot method by a factor of 3.5 to 35.1.
    • Enables filtering with multiple S.E.s in a single operator with reduced computational cost.

    Conclusions:

    • The proposed algorithm offers significant computational advantages for grayscale morphological operations.
    • The ability to perform multi-S.E. filtering in a single step enhances suitability for applications like granulometries and template matching.
    • This method provides a more efficient approach to fundamental image processing tasks.