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 Concept Videos

IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

2.3K
IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
2.3K
Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

7.2K
When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
Different compounds display unique properties due to their...
7.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

From manganese mineral evolution history to atmospheric oxygen reconstruction.

National science review·2026
Same author

Hetairos is a histology-based artificial intelligence model for predicting central nervous system tumor methylation subtypes.

Nature cancer·2026
Same author

HiAdapter: Histopathology-induced Adapter for Pathology Foundation Models.

IEEE transactions on medical imaging·2026
Same author

Manganese (Hydr)oxides record the dynamic evolution of a million-year Hesperian Ocean in Utopia Planitia, Mars.

Nature communications·2026
Same author

Thermal3D-GS: Physics-Induced 3D Gaussians for Thermal Infrared Novel-View Synthesis With a Large-Scale Dataset.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

Clinical efficacy study of a spherical nasal vestibular stent.

Frontiers in medicine·2026

Related Experiment Video

Updated: Mar 28, 2026

Evaluating Targeting Accuracy in the Focal Plane for an Ultrasound-guided High-intensity Focused Ultrasound Phased-array System
08:08

Evaluating Targeting Accuracy in the Focal Plane for an Ultrasound-guided High-intensity Focused Ultrasound Phased-array System

Published on: March 6, 2019

5.7K

Infrared Ship Target Segmentation Based on Spatial Information Improved FCM.

Xiangzhi Bai, Zhiguo Chen, Yu Zhang

    IEEE Transactions on Cybernetics
    |December 17, 2015
    PubMed
    Summary

    This study introduces an improved fuzzy C-means (FCM) clustering method for segmenting infrared (IR) ship images. The enhanced approach effectively handles noise and intensity variations, outperforming existing methods for accurate IR ship target segmentation.

    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

    3.7K
    Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
    14:08

    Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

    Published on: April 13, 2013

    43.8K

    Related Experiment Videos

    Last Updated: Mar 28, 2026

    Evaluating Targeting Accuracy in the Focal Plane for an Ultrasound-guided High-intensity Focused Ultrasound Phased-array System
    08:08

    Evaluating Targeting Accuracy in the Focal Plane for an Ultrasound-guided High-intensity Focused Ultrasound Phased-array System

    Published on: March 6, 2019

    5.7K
    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

    3.7K
    Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
    14:08

    Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

    Published on: April 13, 2013

    43.8K

    Area of Science:

    • Computer Vision
    • Image Processing
    • Artificial Intelligence

    Background:

    • Infrared (IR) ship image segmentation is challenging due to noise and intensity inhomogeneity.
    • Traditional fuzzy C-means (FCM) clustering lacks spatial information consideration and is sensitive to noise.

    Purpose of the Study:

    • To propose an improved FCM method for robust IR ship target segmentation.
    • To enhance segmentation accuracy by incorporating spatial information and refining constraints.

    Main Methods:

    • Developed an improved FCM algorithm integrating nonlocal spatial information of ship targets.
    • Utilized Markov random field to refine local spatial constraints using contour shape information.
    • Initialized the improved FCM with K-means results for faster convergence.

    Main Results:

    • The proposed method demonstrates superior performance in segmenting IR ship images.
    • Experimental results show significant improvements over existing FCM and other methods.
    • The enhanced FCM effectively addresses noise and intensity variations in IR imagery.

    Conclusions:

    • The improved FCM method offers a more effective solution for IR ship target segmentation.
    • Incorporating spatial and shape information enhances segmentation robustness and accuracy.
    • This approach provides a valuable advancement for maritime surveillance and target recognition.