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 Video

Updated: Jul 7, 2026

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
07:05

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Published on: February 15, 2022

Automatic target segmentation by locally adaptive image thresholding.

W N Lie1

  • 1Dept. of Comput. Sci. and Inf. Eng., Yuan-Ze Inst. of Technol., Taoyuan.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1995
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 journal

LSR-Diff: A Diffusion Model Synthesizing Level Set Representations for Reliable Segmentation of Medical Images with Ambiguous Edges.

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

SinColor: Uncertainty-Guided Single-Step Diffusion for Image Colorization.

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

Through the Looking Glass: A Dual Perspective on Weakly-Supervised Few-Shot Segmentation.

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

This study introduces a novel adaptive thresholding algorithm for improved target extraction, especially for small, low-contrast targets. The method enhances detection accuracy in challenging, noisy backgrounds.

Area of Science:

  • Image Processing
  • Computer Vision
  • Pattern Recognition

Background:

  • Conventional histogram-based and global thresholding methods struggle with detecting small, low-contrast targets.
  • Space-varying noise and clutter significantly degrade the performance of existing target extraction techniques.

Purpose of the Study:

  • To propose a locally adaptive thresholding algorithm for robust target extraction.
  • To overcome the limitations of conventional methods in detecting small, low-contrast targets.
  • To enhance target detection in the presence of noise and clutter.

Main Methods:

  • Introduced a shape connectivity measure based on co-occurrence statistics for adaptive threshold evaluation.
  • Developed a no-target identification procedure to model a local-processing paradigm.

More Related Videos

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Related Experiment Videos

Last Updated: Jul 7, 2026

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures
07:05

Area-based Image Analysis Algorithm for Quantification of Macrophage-fibroblast Cocultures

Published on: February 15, 2022

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

  • Implemented adaptive threshold determination to handle space-varying noise and clutter.

    • Main Results:

    • The proposed algorithm effectively extracts targets from complex backgrounds.
    • Demonstrated superior performance compared to manual global thresholding operations.
    • Achieved reliable target detection even with space-varying noise and clutter.

    Conclusions:

    • The novel locally adaptive thresholding algorithm offers a significant improvement for target extraction.
    • The method is particularly effective for small targets with low contrast in noisy environments.
    • This approach provides a more robust and accurate solution than traditional methods.