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

Multiscale morphological segmentation of gray-scale images.

Susanta Mukhopadhyay1, Bhabatosh Chanda

  • 1Burnham Inst., La Jolla, CA 92037, USA. susanta@burnham.org

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 2, 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

Multiple Pyramids Based Image Inpainting Using Local Patch Statistics and Steering Kernel Feature.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2019
Same author

Learning a Patch Quality Comparator for Single Image Dehazing.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2018
Same author

A Group-Based Image Inpainting Using Patch Refinement in MRF Framework.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2017
Same author

A fuzzy-rule-based approach for single frame super resolution.

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

Super resolution image reconstruction through Bregman iteration using morphologic regularization.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2012
Same author

Exploratory analysis of brain connectivity with ICA.

IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society·2006
Same journal

Mask-guided Asymmetric Contrastive and Semantic Alignment for Unsupervised Person Re-Identification.

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

This study introduces a novel multiscale morphological image segmentation method. The approach effectively segments gray level images by reconstructing features at various scales, outperforming standard methods.

Area of Science:

  • Computer Vision
  • Image Processing
  • Digital Image Analysis

Background:

  • Image segmentation is crucial for analyzing image content.
  • Traditional methods like watershed algorithms can suffer from over-segmentation.
  • Multiscale analysis is essential for capturing features at different resolutions.

Purpose of the Study:

  • To propose a new method for segmenting gray level images using multiscale morphology.
  • To address over-segmentation issues common in image segmentation.
  • To integrate segments extracted at various scales for a comprehensive result.

Main Methods:

  • The proposed method employs multiscale morphological closing and opening by reconstruction.
  • It utilizes an isotropic structuring element for feature extraction.

Related Experiment Videos

  • The algorithm incorporates criteria for segment detection (growing, merging, saturation) across multiple scales.

    • Main Results:

    • The method was tested on synthetic and real gray level images.
    • Results were compared quantitatively against standard image segmentation techniques.
    • The approach demonstrated effective segmentation by integrating features from various scales.

    Conclusions:

    • The proposed multiscale morphological approach offers a robust solution for gray level image segmentation.
    • It successfully handles image features at different scales, mitigating over-segmentation.
    • The method provides a competitive alternative to existing segmentation algorithms.