Quality control is a key requirement in the industrial production of textiles. This can be carried out manually through visual inspection or automatically using computer vision technologies. The higher the level of automation, the greater the percentage of production that can be effectively monitored. Artificial vision enables faster inspection and makes it possible to examine the entire output with consistent performance and reliability.
Artificial Vision for Textile quality control
What you'll learn
Modern quality control methods.
Use of artificial vision in textile inspection.
Fundamentals of computer vision applied to fabrics.
Common defect types in woven textiles.
Automatically detectable defects using vision systems.
Key analytical principles and techniques.
Relevant defect-detection algorithms.
Practical steps for implementing automated inspection systems.
Skills you'll gain
- Image Analysis
- Image Quality
- Quality Control
- Digital Signal Processing
- AI literacy
- Structural Analysis
- Machine Learning Methods
- Computer Hardware
- Automation Engineering
- Data Preprocessing
- Artificial Intelligence and Machine Learning (AI/ML)
- Failure Analysis
- Manufacturing and Production
- Anomaly Detection
- Quality Assurance
- Computer Vision
Details to know
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Assessments
77 assignments
Taught in English
Recently updated!
June 2026
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There are 5 modules in this course
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