Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Mechanical Characteristics of Steel

Mechanical Characteristics of Steel

The mechanical characteristics of steel are assessed through various tests that evaluate its strength, toughness, and flexibility. These tests include tension, torsion, impact, bending, and hardness assessments, each providing crucial information about steel's suitability for specific applications.
The tension test is fundamental for determining tensile strength. In this test, a steel specimen is stretched using a gripping device until it breaks. The data collected during this test are used...

Steel Manufacturing

Steel Manufacturing

Steel manufacturing is a multi-stage process that begins by smelting iron ore into cast iron in a blast furnace. This initial stage involves layering iron ore with coke, a type of fuel, and crushed limestone within the furnace. The coke is ignited with a high volume of air, leading to the creation of carbon monoxide, which acts to reduce the iron ore to pure iron.
During this smelting process, limestone plays a crucial role by forming slag. Slag captures impurities within the molten iron, such...

Lumber Defects

Lumber Defects

Lumber defects, which can affect both the appearance and structural integrity of wood, include a variety of growth and manufacturing flaws. Growth defects such as knots and knotholes occur where branches were once attached to the tree trunk, with knotholes forming when these knots fall out. Other natural defects include decay and insect damage, which compromise the wood's strength and durability.
Shakes are minor fractures that run along or across the wood's annual rings, while wane is...

Steel Fastening Techniques

Steel Fastening Techniques

Steel sections can be joined together through various fastening techniques including riveting, bolting, and welding, each suitable for different structural requirements and conditions.
Rivets are cylindrical steel fasteners with a specially designed head. During application, rivets are heated until white-hot and then inserted through pre-drilled holes in the steel sections. A pneumatic hammer is used to shape the exposed end into a second head, securing the sections together.
Bolting is another...

Structural Steel Products

Structural Steel Products

Structural steel products are created within a structural mill. The process begins with a beam blank that is reheated and then fed through a series of rollers. These rollers progressively shape the metal into its final form. Adjusting the spacings between the rollers allows for the production of different sections with the same nominal dimensions.
Once shaped, the steel's final form emerges as a continuous length, which is then segmented by a hot saw into manageable pieces. These segments...

You might also read

Related Articles

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

Sort by

Same author

MDFNet: an unsupervised lightweight network for ear print recognition.

Journal of ambient intelligence and humanized computing·2022

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 4, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

Wavelet Texture Descriptor for Steel Surface Defect Classification.

Djilani Belila^1,2, Belal Khaldi^1,2, Oussama Aiadi^1,2

¹Department of Computer Science and Information Technologies, University of Kasdi Merbah, Ouargla 30000, Algeria.

Materials (Basel, Switzerland)

|December 17, 2024

Summary

This summary is machine-generated.

This study introduces a new method using wavelet transform and texture descriptors for accurate steel surface defect classification. It achieves high accuracy, even with limited data, improving industrial quality control.

Keywords:

image classification industry image analysis multiscale wavelet decomposition steel surface defect texture analysis wavelet texture descriptor

More Related Videos

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

Published on: July 19, 2016

Related Experiment Videos

Last Updated: Jun 4, 2025

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines

Published on: January 5, 2024

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography

Published on: May 15, 2017

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

Published on: July 19, 2016

Area of Science:

Materials Science
Computer Vision
Image Processing

Background:

Accurate steel surface defect classification is vital for product quality and cost reduction in manufacturing.
Existing methods may struggle with precision and efficiency in diverse defect scenarios.

Purpose of the Study:

To develop a novel, robust, and precise method for steel surface defect classification.
To leverage wavelet transform and texture descriptors for enhanced feature extraction.

Main Methods:

Image decomposition using multi-level wavelet transforms.
Extraction of statistical and textural features from wavelet coefficients.
Recursive Feature Elimination (RFE) for optimal feature selection.

Main Results:

Achieved 99.67% accuracy on the NEU-CLS dataset and 98.24% on the X-SDD dataset.
Demonstrated superior performance compared to state-of-the-art techniques.
Maintained high accuracy in limited data scenarios, proving robustness.

Conclusions:

The proposed wavelet transform and texture descriptor method offers effective and precise steel surface defect classification.
The method's robustness and high accuracy make it suitable for practical industrial applications.
This approach enhances quality control and reduces production costs in the steel industry.