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

Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

519
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
519
Confocal Fluorescence Microscopy01:16

Confocal Fluorescence Microscopy

19.9K
Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...
19.9K

You might also read

Related Articles

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

Sort by
Same author

GMRVGG: A Bearing Fault Diagnosis Method Based on Tri-Modal Image Feature Fusion.

Sensors (Basel, Switzerland)·2026
Same author

Advanced Fault Diagnosis and Health Monitoring Techniques for Complex Engineering Systems: 2nd Edition.

Sensors (Basel, Switzerland)·2025
Same author

YOLO-HVS: Infrared Small Target Detection Inspired by the Human Visual System.

Biomimetics (Basel, Switzerland)·2025
Same author

Controlling fluid flow rate to separate leukocytes and cancer cells based on stiffness differences.

Mikrochimica acta·2025
Same author

Low Noise Feed-Through Compensation Circuit Design for Resonant MEMS Pressure Sensor.

Micromachines·2025
Same author

Close atomic surface on aluminum alloy achieved by a near-neutral novel green chemical mechanical polishing method with high material removal rate.

Nanoscale·2025
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jan 13, 2026

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
11:34

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

11.5K

Two-Dimensional Image Lempel-Ziv Complexity Calculation Method and Its Application in Defect Detection.

Jiancheng Yin1, Wentao Sui1, Xuye Zhuang1

  • 1School of Mechanical Engineering, Shandong University of Technology, Zibo 255049, China.

Entropy (Basel, Switzerland)
|October 28, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel two-dimensional Lempel-Ziv complexity (LZC) for image analysis, extending its use beyond one-dimensional time series. The method achieves 100% accuracy in defect detection, demonstrating its effectiveness for image pattern analysis.

Keywords:
Lempel–Ziv complexitydefect detectionlocal receptive fieldtwo-dimensional image

More Related Videos

Comprehensive Characterization of Extended Defects in Semiconductor Materials by a Scanning Electron Microscope
11:14

Comprehensive Characterization of Extended Defects in Semiconductor Materials by a Scanning Electron Microscope

Published on: May 28, 2016

14.3K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.6K

Related Experiment Videos

Last Updated: Jan 13, 2026

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
11:34

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

11.5K
Comprehensive Characterization of Extended Defects in Semiconductor Materials by a Scanning Electron Microscope
11:14

Comprehensive Characterization of Extended Defects in Semiconductor Materials by a Scanning Electron Microscope

Published on: May 28, 2016

14.3K
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
13:44

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns

Published on: August 30, 2013

43.6K

Area of Science:

  • Computer Vision
  • Image Processing
  • Pattern Recognition

Background:

  • Lempel-Ziv complexity (LZC) is effective for analyzing one-dimensional time series but not directly applicable to 2D images.
  • Existing methods lack the ability to analyze complex patterns within image data directly.

Purpose of the Study:

  • To develop a two-dimensional Lempel-Ziv complexity (LZC) method for analyzing 2D images.
  • To extend the application of LZC to image analysis and defect detection.
  • To improve the identification of independent pattern changes in images.

Main Methods:

  • Combined LZC with the local receptive field concept from convolutional neural networks.
  • Normalized image pixels and size, then encoded based on 4x4 region value sorting.
  • Rearranged image encoding into a vector for LZC calculation.
  • Integrated with dilation and Sobel operators for defect detection.

Main Results:

  • Successfully extended LZC to two-dimensional images.
  • Demonstrated effective identification of independent pattern changes in images.
  • Achieved 100% accuracy in practical defect detection cases.

Conclusions:

  • The proposed 2D LZC method broadens the application scope of LZC to image analysis.
  • The method is effective for defect detection, offering high accuracy.
  • This approach provides a new tool for analyzing complex patterns in image data.