Computer Vision-Based Detection of Patterns in Textile Microscopy Images

The analysis and detection of patterns in textile materials are a critical challenge in modern manufacturing, quality control, and automation processes. Traditional inspection methods, often reliant on manual observation, are not only time-consuming but also prone to inconsistencies. The need for a more precise, efficient, and scalable approach has driven interest in leveraging computer vision for this task. Computer vision systems, powered by advanced algorithms and machine learning models, offer the ability to process and interpret visual data from textile images at high speeds and with greater accuracy.

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Publication Details

Journal
The Annals of “Dunarea de Jos” University of Galati Fascicle IX Metallurgy and Materials Science
Published
2025-06-15
DOI
https://doi.org/10.35219/mms.2025.2.01
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Computer Vision-Based Detection of Patterns in Textile Microscopy Images

Mihaela MARIN, Florin-Bogdan MARIN
The Annals of “Dunarea de Jos” University of Galati Fascicle IX Metallurgy and Materials Science
Industrial Vision Systems and Defect Detection
article

Computer Vision-Based Detection of Patterns in Textile Microscopy Images

Mihaela MARIN, Florin-Bogdan MARIN
article en

Abstract

The analysis and detection of patterns in textile materials are a critical challenge in modern manufacturing, quality control, and automation processes. Traditional inspection methods, often reliant on manual observation, are not only time-consuming but also prone to inconsistencies. The need for a more precise, efficient, and scalable approach has driven interest in leveraging computer vision for this task. Computer vision systems, powered by advanced algorithms and machine learning models, offer the ability to process and interpret visual data from textile images at high speeds and with greater accuracy.

The Annals of “Dunarea de Jos” University of Galati Fascicle IX Metallurgy and Materials ScienceVol. 48(2)
"Dunarea de Jos" University of Galati (RO)
Openalex Percentile: Top 62%
Industrial Vision Systems and Defect Detection
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