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

Three-Dimensional Analysis of Strain01:29

Three-Dimensional Analysis of Strain

798
Three-dimensional strain analysis is crucial for understanding how materials deform under stress, particularly in elastic, homogeneous materials. This method employs principal stress axes to simplify complex stress states into more understandable forms. Subjected to stress, a small cubic element within a material either expands or contracts along these axes, transforming into a rectangular parallelepiped. This transformation effectively illustrates the material's deformation. The principal...
798
Imperfections in Crystal Structure: Point, Line and Plane Defects01:25

Imperfections in Crystal Structure: Point, Line and Plane Defects

156
A perfect crystal, in theory, has a uniform structure with the same unit cell and lattice points throughout. However, any deviation from this periodic arrangement is known as an imperfection or defect. These defects can be categorized into three types: point, line, and plane defects.Point defects occur when there is a deviation from the ideal due to missing atoms, displaced atoms, or additional atoms. These imperfections might occur due to imperfect packing during crystallization or because of...
156

You might also read

Related Articles

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

Sort by
Same author

Exploring the neuroprotective mechanism of lumbrokinase against ischemic stroke based on network pharmacology, molecular docking and experimental validation.

Journal of ethnopharmacology·2026
Same author

Integrating Divergence-Based Proteomic Analysis and Directed Network Diffusion to Characterize Diagnosis-Anchored Molecular Variability at the Metabolic Syndrome-Migraine Interface.

International journal of molecular sciences·2026
Same author

Evaluation of randomized controlled trial literature in traditional Chinese medicine: a literature quality assessment system.

Trials·2026
Same author

Evaluating Large-Scale and Lightweight Large Language Models for Traditional Chinese Medicine Exam Questions: A Comparative Study.

Journal of evidence-based medicine·2026
Same author

What Substitution and Prediction Strategies Address the Challenge of an Unmeasurable C2-7 Cobb Angle?

Clinical orthopaedics and related research·2026
Same author

The mediating and moderating roles of physical sub-health in the relationship between family functioning and mental health problems among Chinese adolescents.

BMC public health·2026

Related Experiment Video

Updated: May 6, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

15.6K

A dataset for surface defect detection on complex structured parts based on photometric stereo.

Lin Wu1, Yu Ran1, Li Yan2

  • 1School of Life Sciences, Beijing University of Chinese Medicine, Beijing, 102488, China.

Scientific Data
|February 16, 2025
PubMed
Summary

A new deep learning method improves automated optical inspection (AOI) for metal surfaces by using photometric stereo vision and a novel image acquisition technique. This approach enhances defect detection accuracy, reducing errors on challenging non-planar parts.

More Related Videos

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

11.1K
Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

1.9K

Related Experiment Videos

Last Updated: May 6, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

15.6K
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

11.1K
Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery
05:12

Robotized Testing of Camera Positions to Determine Ideal Configuration for Stereo 3D Visualization of Open-Heart Surgery

Published on: August 12, 2021

1.9K

Area of Science:

  • Computer Vision
  • Machine Learning
  • Materials Science

Background:

  • Automated Optical Inspection (AOI) is vital for industrial quality control.
  • Traditional AOI faces challenges with shadows, reflectivity, and non-planar surfaces, leading to detection inaccuracies.

Purpose of the Study:

  • To develop a novel defect detection technique for metal surfaces overcoming AOI limitations.
  • To create a comprehensive dataset for training and validating deep learning models for metal surface defect detection.

Main Methods:

  • Proposed a Stroboscopic Illuminant Image Acquisition (SIIA) method combining photometric stereo vision and deep learning.
  • Developed a Taylor Series Channel Mixer (TSCM) to create pseudo-color images from multi-angle illuminations.
  • Utilized hue randomization for data augmentation and validated object detection models (FCOS, YOLOv5, YOLOv8, RT-DETR) on the Metal Surface Defect Dataset (MSDD).

Main Results:

  • Achieved a mean Average Precision (mAP) of 86.1% on the MSDD, outperforming traditional methods.
  • The proposed technique effectively handles shadows and reflectivity issues inherent in AOI.
  • The MSDD comprises 138,585 single-channel and 9,239 mixed images covering eight defect types.

Conclusions:

  • The novel deep learning and photometric stereo vision approach significantly enhances automated visual inspection of metal surfaces.
  • The developed MSDD provides a valuable resource for advancing research in industrial defect detection.
  • The method offers a robust solution for end-to-end defect detection using universal object detectors.