Developing an Interactive MATLAB-Based Application for AI-Enhanced Defect Detection in Steel Images

In the area of manufacturing, ensuring the integrity of structural elements of steel parts is important for safety and quality control The traditional systems of defect detection in steel structures are based predominantly on manual inspection, which is time-consuming and human error chances are quite probable In this work, a new interactive MATLAB-based application is presented that employs AI to improve defects identification in steel images The tool enables users to select and interactively analyze images through synthetic steel image generation followed by feature extraction using Histogram of Oriented Gradients (HOG) and classification using Support Vector Machine (SVM) This study describes the process of the development of the application, outlines its implementation and assesses its performance based on user-interaction The initial findings indicate the capability of the tool to enhance the precision, and cost-effectiveness of defect detection processes, which further substantiates automated and dependable inspection in professional environments.

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Publication Details

Published
2024-08-08
DOI
https://doi.org/10.1109/iccpct61902.2024.10673316
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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article

Developing an Interactive MATLAB-Based Application for AI-Enhanced Defect Detection in Steel Images

Swetha
Industrial Vision Systems and Defect Detection
article

Developing an Interactive MATLAB-Based Application for AI-Enhanced Defect Detection in Steel Images

Swetha
article en

Abstract

In the area of manufacturing, ensuring the integrity of structural elements of steel parts is important for safety and quality control The traditional systems of defect detection in steel structures are based predominantly on manual inspection, which is time-consuming and human error chances are quite probable In this work, a new interactive MATLAB-based application is presented that employs AI to improve defects identification in steel images The tool enables users to select and interactively analyze images through synthetic steel image generation followed by feature extraction using Histogram of Oriented Gradients (HOG) and classification using Support Vector Machine (SVM) This study describes the process of the development of the application, outlines its implementation and assesses its performance based on user-interaction The initial findings indicate the capability of the tool to enhance the precision, and cost-effectiveness of defect detection processes, which further substantiates automated and dependable inspection in professional environments.

Vol. 789
Karnataka State Women's University (IN)
Openalex Percentile: Top 78%
Industrial Vision Systems and Defect Detection
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Developing an Interactive MATLAB-Based Application for AI-Enhanced Defect Detection in Steel Images — Swetha · (2024) | TGRS Research Map | TGRS